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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The Role of Biofuels and Biomass Feedstocks for Decarbonizing the U.S. Economy by 2050 - (DECARB) Decarbonizing Energy Through Collaborative Analysis of Routes and Benefits

Utilizing biomass resources, such as cellulosic biomass and waste, can greatly contribute to decarbonization efforts in the U.S. economy. The U.S. bioenergy sector includes corn ethanol production, biodiesel, renewable diesel production, and the utilization of biomass wastes for electricity generation being the primary applications. Within the electricity sector, biopower can play a crucial role as a stable low-carbon resource. Enhancing the electricity mix's diversity could enhance grid reliability. If the issues regarding hot gas cleanup can be resolved, flexible biopower resources like biomass gasification facilities could complement the integration of variable renewable energy sources due to their quick ramp-up and ramp-down times. The criticality of bioenergy deployment lies in its ability to decarbonize hard-to-electrify sectors, such as aviation, where alternative decarbonization options may not be viable in the short term. Moreover, bioenergy has the potential to be converted into process heating, building materials, and plastics, which are not considered in this study. A set of pathways was carefully chosen to represent viable options for converting ample herbaceous and woody cellulosic feedstocks into fuels, chemicals, and electricity in this study. In conclusion, biomass pathways provide flexibility by generating various types of bioenergy and bioproducts, including electricity, hydrogen, liquid fuels, biochemicals, and bioplastics. When paired with carbon dioxide capture and storage (CCS), specific bioenergy approaches can effectively extract carbon dioxide from the atmosphere, thus providing an effective decarbonization option for the transportation sector.

09 BIOMASS FUELS↗
DOE OSTI2022

Synthesis and Analysis of Performance-Advantaged Bioproducts

Performance-advantaged bioproducts (PABPs) are "novel products where the bio-based product does not resemble an existing petroleum-derived molecule but offers a performance advantage over existing products" (Fitzgerald, Bailey 2018). PABPs are an exciting area with near-term potential to accelerate the bioeconomy. We focus on synthesis, characterization, and economic and sustainability analyses for PABPs, aiming to leverage the inherent chemical functionality of molecules from carbohydrates and lignin via chemical and biological transformations. We collaborate with other BETO projects to source new molecules. Our work is integrated with the Inverse Design project, which provides computational predictions for PABPs and first principles-based results to explain observed properties. Primary outcomes include 1) a Nature Reviews Materials paper that establishes PABP design principles, 2) PA nylons from beta-ketoadipic acid, 3) new recyclable thermosets from bio-aromatic amines, 4) new PA plasticizers that are less toxic, and 5) the experimental validation of a machine learning tool, PolyML, from the Inverse Design project. Going forward, we are working towards an integrated framework to dramatically narrow PABP design space and a materials flow analysis of commodity chemicals as a benchmark for PABPs. Our main challenges are in the sourcing of new molecules that are not commercially available and the need for comprehensive characterizations and scale-up for technology transfer.

BIOMASS FUELS↗
DOE OSTI2024

DEVELOPMENT AND DEMONSTRATION TESTBED FOR THE REMOTE OPERATIONS AND MONITORING OF MICROREACTORS

The nuclear industry is rapidly developing many advanced-reactor concepts for near-term deployment in both traditional and non-traditional nuclear-powered applications. One such category of advanced reactor is the microreactor, a class of reactor with less than 20MWth power output, intended for applications where the economics or logistics of traditional power sources are difficult. This includes applications such as remote communities, mining sites, defense installations, or humanitarian and disaster-relief missions. One key enabling feature for the successful deployment of microreactors is a remote operations capability. Remote operations provide monitoring and control capabilities which can significantly reduce staffing costs by eliminating the need for licensed operators at each reactor facility and improve the economic viability for microreactor deployment. A remote concept of operations is not currently an established capability in the nuclear industry. In addition, no demonstration microreactor is expected to complete construction or go critical until at least 2026. This leaves two major capability gaps: the successful demonstration of a remote concept of operations for microreactors and a test bed suitable for said demonstration. Both gaps must be addressed in order to advance the remote concepts of nuclear operation and, more broadly, microreactors themselves from paper to reality. This paper aims to fill these gaps and describes a test bed that would support development and deployment of a remote concept of nuclear operations, initial experimental results from that test bed, and the application of the test bed and experimental results for a digital-twin-based remote concept of operations underdevelopment at Idaho National Laboratory (INL). The platform chosen as a remote concept of nuclear operations test bed is the Single Primary Heat Extraction and Removal Emulator, known as SPHERE, located at INL. SPHERE is a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The small-scale and non-nuclear nature of SHPERE limit safety concerns associated with remote operations while still providing the physical response representative of a microreactor. A network connection was added to SPHERE that enables remote-monitoring capability. This allows for real-time data streaming to networked workstations, data historians, and human-machine interfaces (HMIs). These are all critical components in a remote concept of operations, thus providing a robust development and demonstration platform. An initial experiment was performed using the SPHERE remote operations testbed. This included running a comprehensively instrumented SPHERE through a series of steady-state and transient operating scenarios in both normal and abnormal operating conditions, all while streaming live test data to a remote HMI and data warehouse. This initial experiment served three purposes: (1) characterizing the response of SPHERE, (2) demonstrating the remote connection to SPHERE, and (3) providing a baseline data set for development of a digital-twin-based remote concept of operations that is under development at INL.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Getting allometry right at the Oak Ridge free‐air CO 2 enrichment experiment: Old problems and new opportunities for global change experiments

Societal Impact Statement Free‐air CO 2 enrichment (FACE) experiments provide essential data on forest responses to increasing atmospheric CO 2 for evaluations of climate change impacts on humanity. Understanding and reducing the uncertainty in the experimental results is critical to ensure scientific and public confidence in the models and policy initiatives that derive therefrom. One source of uncertainty is the estimation of tree biomass using mathematical relationships between biomass and easily obtained and non‐destructive measurements (allometry). We evaluated the robustness of the allometric relationships established at the beginning of a FACE experiment and discuss the challenges and opportunities for the new generation of FACE experiments. Summary Long‐term field experiments to elucidate forest responses to rising atmospheric CO 2 concentration require allometric equations to estimate tree biomass from non‐destructive measurements of tree size. We analyzed whether the allometric equations established at the beginning of a free‐air CO 2 enrichment (FACE) experiment in a Liquidambar styraciflua plantation were still valid at the end of the 12 year experiment. Aboveground woody biomass was initially predicted by an equation that included bole diameter, taper, and height, assuming that including taper and height as predictors would accommodate changes in tree structure that might occur over time and in response to elevated CO 2 . At the conclusion of the FACE experiment, we harvested 23 trees, measured dimensions and dry mass of boles and branches, and extracted and measured the woody root mass of 10 trees. Although 10 of the harvested trees were larger than the trees used to establish the allometric relationship, measured aboveground woody biomass was well predicted by the original allometry. The initial linear equation between bole basal area and woody root biomass underestimated final root biomass by 28%, but root biomass was just 21% of total wood mass, and errors in aboveground and belowground estimates were offsetting. The allometry established at the beginning of the experiment provided valid predictions of tree biomass throughout the experiment. New allometric approaches using terrestrial laser scanning should reduce an important source of uncertainty in decade‐long forest experiments and in assessments of centuries‐long forest biomass accretion used in evaluating carbon offsets and climate mitigation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enhanced Large-Signal Stability Method for Grid-Forming Inverters During Current Limiting: Preprint

Grid-forming (GFM) inverters are a promising technology for the widespread integration of renewable energy sources in future power systems. As a key element of GFM inverter control, the primary controller governs the internal reference voltage and angle. During contingencies in the grid---such as faults, voltage drops, or frequency and phase jumps---an inverter can be forced into a current-limiting mode of operation modulating inverter dynamics, and, as a result, it is prone to losing synchronism with the grid. In this paper, we propose a novel GFM primary control method with an additional synchronization term that naturally activates during contingencies to improve the dynamic response. The method allows the inverter to remain synchronized with the grid, which improves the inverter's dynamic behavior both during and after current-limiting grid conditions and enhances grid support, including voltage support using full current capacity. The method is demonstrated for voltage, frequency, and phase jumps both in a single-machine-to-infinite-bus and a network-wide electromagnetic transient simulation of the IEEE 14-bus system with 5 GFM inverters. The simulations provide insights into the proposed synchronization method and confirm the high potential of the method, which robustly secures synchronism under severe contingencies.

current limiting↗
DOE OSTI2022

Development of an open-source segmented blade design tool

As wind turbines continue to grow ever larger to reduce the cost of energy, their blades follow suit, with the largest commercial offshore blades extending past 100 m. Massive blades such as these raise key transportation and manufacturing challenges, especially for land-based turbines. Segmented blades are one solution and are garnering increased industry and research interest. In this work, a detailed mechanical joint model is integrated into the Wind-Plant Integrated System Design and Engineering Model (WISDEM ® ), which will facilitate future segmented blade research and optimization. WISDEM is used to design a wind turbine with 100-m segmented blades. This wind turbine design is compared to other machines with 100-m monolithic blades designed for rail-transportability. The designs are compared in terms of blade mass and cost, turbine capital cost, annual energy production, and levelized cost of energy, with monolithic designs being the lightest and most economical. However, this result may vary by wind plant location. A variety of segmentation joint types exist, and they will inevitably vary in parameters such as cost, spanwise location, and physical characteristics. This work examines the sensitivity of wind turbine design drivers and annual energy production to a variety of the aforementioned parameters, using the open-source wind turbine design codes OpenFAST and WISDEM, finding that joint mass, stiffness, and location can have significant effects on design drivers.

17 WIND ENERGY↗
DOE OSTI2021

Functionalized Embedded Monometallic Nickel Catalysts for Enhanced Hydrogen Evolution: Performance and Stability

Viable anionic exchange membrane (AEM) electrolysis for H 2 production requires highly active hydrogen evolution reaction (HER) catalysts that are also robust and cost-effective. Traditionally juxtaposition of two transition metals with one being more oxophilic is necessary for easier access to water in the inner Helmholtz plane as a source of protons in the crucial Volmer step for enhanced HER activity. However, they are prone to passivation at anodic potentials or deactivation via the formation of sub-surface metal hydrides at high cathodic overpotentials. Here we report a method of enabling close juxtaposition of Ni-Ni-oxide surfaces by functionalizing Ni-based catalysts via the careful thermal treatment of carbon-supported Ni nano-particles chelated with a select organic chelating compound referred to as cupferron. This functionalization results in an embedded Ni surface with a clear graphitic coating engendering long-term stability for passivation and subsurface hydride formation. The stability and activity of the functionalized Ni catalyst are demonstrated in half-cell RDE and full-cell AEM membrane-based hydrogen pump experiments. In the case of the latter, the functionalized Ni outperforms carbon-supported Pt.

25 ENERGY STORAGE↗
DOE OSTI2021

Superconducting RF Gun with High Current and the Capability to Generate Polarized Electron Beams

High-current low-emittance CW electron beams are indispensable for nuclear and high-energy physics fixed target and collider experiments, cooling high energy hadron beams, generating CW beams of monoenergetic X-rays (in FELs) and gamma-rays (in Compton sources). Polarization of electrons in these beams provides extra value by opening a new set of observables and frequently improving the data quality. We report on the upgrade of the unique and fully functional CW SRF 1.25 MeV SRF gun, built as part of the Coherent electron Cooling (CeC) project, which has demonstrated sustained CW operation with CsK2Sb photocathodes generating electron bunches with record-low transverse emittances and record-high bunch charge exceeding 10 nC. We propose to extend the capabilities of this system to high average current of 100 milliampere in two steps: increasing the current 30-fold at each step with the goal to demonstrate reliable long-term operation of the high-current low-emittance CW SRF guns. We also propose to test polarized GaAs photocathodes in the ultra-high vacuum (UHV) environment of the SRF gun, which has never been successfully demonstrated in RF accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Identifying human failure events (HFEs) for external hazard probabilistic risk assessment

In recent years, several advancements in nuclear power plant (NPP) probabilistic risk assessment (PRA) have been driven by increased understanding of external hazards, plant response, and uncertainties. However, major sources of uncertainty associated with external hazard PRA remain. One important source is how risk-significant human actions that are carried out to enable plant response and recovery from natural hazards cause the close coupling of physical impacts on plants and overall plant risk during these hazard events. This makes human reliability and human-plant interactions important elements to consider in resolving PRA gaps in external hazards. One of the challenges in considering human response in external hazard probabilistic risk assessment (XHPRA) is that most existing human reliability analysis (HRA) models were not developed for assessing actions outside the control room (termed ex-control room actions) and hazard response. To support this new scope, HRA models will need to be developed or modified to support identification of human activities, causal factors, and uncertainties inherent in external hazard response, thereby providing insights regarding event timing and physical event conditions as they relate to human performance. In this study, there are two main objectives: (1) evaluate the applicability of an existing cognitive-based HRA method, Phoenix, to ex-control room actions, and (2) identify sources of uncertainty to be characterized or reduced in order to make this method suitable for XHPRA. The first step of such work is performed by assessing the suitability of existing HRA methods to support identifying human failure events (HFEs) for human response to flooding hazards. These HFEs are human actions or inactions that are involved in human responses to flooding hazards and could contribute to the loss of a critical function for the plant in the scenario being examined. Here, in this work, decomposition analyses using the cognitive-based Phoenix HRA model are used to identify HFEs. The Phoenix method was found to be suitable for analyzing ex-control room actions as well as identifying specific HFEs and underlying crew failure modes (CFMs). However, the method's suitability for use in ex-control room actions would benefit from expanding the available CFMs to accommodate a larger variety of physical and communication tasks.

42 ENGINEERING↗
DOE OSTI2026

Evolution of storage monitoring – update in response to commercial and regulatory drivers

Carbon Capture and Storage (CCS) is in transition from first-of-a kind projects and research-orientated pilots to commercially-motivated applications. Monitoring results from many newly developed and planned large scale commercial projects are limited; however, it is worthwhile to assess their evolution and consider new strategies as part of an effort to assess and document best practices. Commercial monitoring is targeted to activities that comply with regulatory drivers and de-risk investments. Commercial monitoring also supports accounting that storage has occurred and is tied to project financing. It deals with long time frames and large volumes injected into multiple wells and multiple projects in favorable areas. We see developing trends toward reproducible workflows that systematically reduce risks and clarify expectations for oversight and long-term surveillance. Monitoring techniques showing increasing trends include injection zone pressure as a history-matching and compliance tool. To reduce cost and environmental impact of time-lapse seismic data collection, deploying new approaches and tools, such as use of fibre and installed sources are increasingly applied. Concern over the risk of induced seismicity by regulatory bodies and the general public has increased, which has also resulted in increased monitoring. Some techniques used in the early research phases have been sidelined or used only in restricted applications. For example, geochemical analyses in the injection zone as well as the environment are now being deployed less than it was in research-oriented programs, except in the US where it is required by the permitting process. Expectations of frequent area-wide near surface monitoring have also decreased.

25 ENERGY STORAGE↗
DOE OSTI2020

Climate Sensitivity of Peatland Methane Emissions Mediated by Seasonal Hydrologic Dynamics

Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Peatland emissions are projected to increase under climate change, as rising temperatures and shifting precipitation accelerate microbial metabolic pathways favorable for CH 4 production. However, how these changing environmental factors will impact peatland emissions over the long term remains unknown. Here, we investigate a novel data set spanning an exceptionally long 11 years to analyze the influence of soil temperature and water table elevation on peatland CH 4 emissions. We show that higher water tables dampen the springtime increases in CH 4 emissions as well as their subsequent decreases during late summer to fall. These results imply that any hydroclimatological changes in northern peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if temperature remains unchanged. Furthermore, advancing hydrological understanding in peatland watersheds will be crucial for improving predictions of CH 4 emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A first test of CUPID prototypal light detectors with NTD-Ge sensors in a pulse-tube cryostat

CUPID is a next-generation bolometric experiment aiming at searching for neutrinoless double-beta decay with ~250 kg of isotopic mass of 100 Mo. It will operate at ~10 mK in a cryostat currently hosting a similar-scale bolometric array for the CUORE experiment at the Gran Sasso National Laboratory (Italy). CUPID will be based on large-volume scintillating bolometers consisting of 100 Mo-enriched Li 2 MoO 4 crystals, facing thin Ge-wafer-based bolometric light detectors. In the CUPID design, the detector structure is novel and needs to be validated. In particular, the CUORE cryostat presents a high level of mechanical vibrations due to the use of pulse tubes and the effect of vibrations on the detector performance must be investigated. In this paper we report the first test of the CUPID-design bolometric light detectors with NTD-Ge sensors in a dilution refrigerator equipped with a pulse tube in an above-ground lab. Light detectors are characterized in terms of sensitivity, energy resolution, pulse time constants, and noise power spectrum. Despite the challenging noisy environment due to pulse-tube-induced vibrations, we demonstrate that all the four tested light detectors comply with the CUPID goal in terms of intrinsic energy resolution of 100 eV RMS baseline noise. Indeed, we have measured 70–90 eV RMS for the four devices, which show an excellent reproducibility. We have also obtained high energy resolutions at the 356 keV line from a 133 Ba source, as good as Ge semiconductor γ detectors in this energy range.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

QLiG: Query Like a Graph For Subgraph Matching

A graph is a natural and flexible modeling approach to represent entities and relationships between them in real-world. A Knowledge Graphs (KG) is a specialized graph with formal and structured representation of facts, relationships, annotated with semantic descriptions. Subgraph matching is one of the fundamental graph problems to identify relationships, interactions and activities of interest within a large graph. A query specification is a collection of abstract components, operations, and constraints to express a pattern. The specification can be implemented in different ways based on underlying data model. Various graph query specifications have been developed over the years and have led to the development of different open-sourced and vendor-specific query languages. Such specification are modeled as an extension of relational algebra used to develop relational query languages such as SQL. Such relational concepts do not inherently support graph queries. There is a need to represent graph queries in terms on graph-based components to expedite query construction by non-database experts. We present a graph-based query approach QLiG (pronounced cleeg), to perform subgraph matching in Labeled Property Graph. We present the query specifications, salient features, and a use case to show functional examples.

Purohit, Sumit↗
DOE OSTI2022

Intense infrared lasers for strong-field science

The advent of chirped-pulse amplification in the 1980s and femtosecond Ti:sapphire lasers in the 1990s enabled transformative advances in intense laser–matter interaction physics. Whereas most of experiments have been conducted in the limited near-infrared range of 0.8–1 μm, theories predict that many physical phenomena such as high harmonic generation in gases favor long laser wavelengths in terms of extending the high-energy cutoff. Significant progress has been made in developing few-cycle, carrier-envelope phase-stabilized, high-peak-power lasers in the 1.6–2 μm range that has laid the foundation for attosecond X ray sources in the water window. Even longer wavelength lasers are becoming available that are suitable to study light filamentation, high harmonic generation, and laser–plasma interaction in the relativistic regime. Long-wavelength lasers are suitable for sub-bandgap strong-field excitation of a wide range of solid materials, including semiconductors. In the strong-field limit, bulk crystals also produce high-order harmonics. In this review, we first introduce several important wavelength scaling laws in strong-field physics, then describe recent breakthroughs in short- (1.4–3 μm), mid- (3–8 μm), and long-wave (8–15 μm) infrared laser technology, and finally provide examples of strong-field applications of these novel lasers. Furthermore, some of the broadband ultrafast infrared lasers will have profound effects on medicine, environmental protection, and national defense, because their wavelengths cover the water absorption band, the molecular fingerprint region, as well as the atmospheric infrared transparent window.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

A Simple Model of the Energy Threshold for Snowball Chambers

Cloud and bubble chambers have historically been used for particle detection, capitalizing on supersaturation and superheating, respectively. Here, we present new results from a prototype snowball chamber, in which an incoming particle triggers the crystallization of a purified, supercooled liquid. We demonstrate, for the first time, simulation agreement with our first results from 5 years ago: the higher temperature of the freezing of water and significantly shorter time spent supercooled compared to the control in the presence of a Cf-252 fission neutron source. This is accomplished by combining Geant4 modeling of neutron interactions with the Seitz nucleation model used in superheated bubble chambers, including those seeking dark matter. We explore the possible implications of using this new technology for GeV-scale WIMP searches, especially in terms of spin-dependent proton coupling, and report the first supercooling of WbLS (water-based liquid scintillator).

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Comparing Offshore Wind Energy Procurement and Project Revenue Sources Across U.S. States

The pace of offshore wind energy procurement in the United States has rapidly accelerated in recent years. U.S. states along the Atlantic Coast have set procurement goals for offshore wind energy to meet renewable portfolio standards and serve state policy needs. By the end of 2019, projects with a total capacity of 6.4 gigawatts (GW) had established long-term contracts (or equivalent regulatory requirements) with utility off-takers. The prices established in these contracts since 2017 have been well below expectations from many industry observers, prompting stakeholders to compare price levels across U.S. states and globally. However, comparing procurement prices across projects and jurisdictions is often challenging because of differences in project parameters, support regimes, supply chains, and the applicable tax and regulatory environment. These characteristics provide critical context for understanding project revenue streams, delivery obligations, and risk allocation, which need to be accounted for when comparing across different projects. In combination, variation in these characteristics between projects results in measurable differences in project costs and revenues and, consequently, in different offer bids. In this report, we systematically analyze offshore wind energy support regimes across U.S. states. Because offshore wind energy procurement prices from U.S. projects are often compared not only among states but also with European tenders, this report also provides an overview of support regimes and taxonomy used in European offshore wind markets. The content of this report was derived from a literature review, primarily regulatory filings and summary reports, and 16 interviews with leading industry experts from state agencies, energy sector consultancies, and law practices. The comparison between U.S. states focuses on several dimensions, including statutory authority, solicitation procedures, procurement goals and awards, and the structuring of physical and transactional delivery of energy services.

17 WIND ENERGY↗
DOE OSTI2024

Effects of uranium metal carbon content on hydriding kinetics and corrosion blister number/area at sub-ambient pressures

Carbon is a common impurity in uranium metal, resulting in a number of uranium–carbon inclusion phases that contribute to an increase in metal defect density as carbon content increases. It is widely held that uranium hydride corrosion preferentially nucleates at these defect sites, and that an increase in carbon content will therefore represents an increase in uranium hydride corrosion sites on the metal surface. We hydrided six uranium sources with differing carbon contents to explore whether this assumption holds in a sub-ambient (~ 0.1 atm hydrogen), sealed environment, and report the resulting reaction kinetics and uranium hydride blister benchmarking data. We find that carbon content is not strongly correlated with reaction kinetics terms or the resulting hydride blister number and area, but that there is a tight relationship between corrosion blister number/area and kinetics as is expected. Further, we find that there is a strong trend of decreasing variance in the blister number, blister area, and induction time as carbon content increases (higher carbon content results in more reproducible blister populations). Additionally, we find a narrow band of uranium metal consumption at the end of the parabolic phase of reaction progress (beginning of linear growth phase) of 0.098 ± 0.011 w/w%, a fact that may be useful in assaying hydrogen corrosion of uranium metal within sealed environments generally.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types

In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widespread for information extraction tasks from unstructured clinical notes. Disparities in performance when deploying machine learning models in the real world have recently received considerable attention. In the clinical NLP domain, the robustness of convolutional neural networks (CNNs) for classifying cancer pathology reports under natural distribution shifts remains understudied. In this research, we aim to quantify and improve the performance of the CNN for text classification on out-of-distribution (OOD) datasets resulting from the natural evolution of clinical text in pathology reports. We identified class imbalance due to different prevalence of cancer types as one of the sources of performance drop and analyzed the impact of previous methods for addressing class imbalance when deploying models in real-world domains. Our results show that our novel class-specialized ensemble technique outperforms other methods for the classification of rare cancer types in terms of macro F1 scores. We also found that traditional ensemble methods perform better in top classes, leading to higher micro F1 scores. Based on our findings, we formulate a series of recommendations for other ML practitioners on how to build robust models with extremely imbalanced datasets in biomedical NLP applications.

60 APPLIED LIFE SCIENCES↗