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Record W2790846111 · doi:10.1126/sciadv.aar7180

Critical advancements in achieving high power and stable nonprecious metal catalyst–based MEAs for real-world proton exchange membrane fuel cell applications

2018· article· en· W2790846111 on OpenAlexafffund
Dustin Banham, Takeaki Kishimoto, Yingjie Zhou, Tetsutaro Sato, Kyoung Bai, Jun‐ichi Ozaki, Yasuo Imashiro, Siyu Ye

Bibliographic record

VenueScience Advances · 2018
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsBallard Power Systems (Canada)
FundersBallard Power Systems
KeywordsProton exchange membrane fuel cellCatalysisFuel cellsProtonMetalMembraneMaterials scienceComputer scienceChemical engineeringNanotechnologyChemistryEngineeringOrganic chemistryPhysicsMetallurgy

Abstract

fetched live from OpenAlex

MEA) using a precommercial NPMC. In situ electrochemical analysis of the CCLs is also used to help gain insight into the degradation mechanism observed during galvanostatic testing. Overall, the performance of this NPMC-based MEA has achieved commercial readiness and will be introduced into an NPMC-based product for portable power applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.289
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations270
Published2018
Admission routes2
Has abstractyes

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