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Record W2510242493 · doi:10.1149/07514.0003ecst

(Plenary) Doing More with Less: Challenges for Catalyst Layer Design

2016· article· en· W2510242493 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Transactions · 2016
Typearticle
Languageen
FieldMaterials Science
TopicMachine Learning in Materials Science
Canadian institutionsMcMaster UniversityAutomotive Fuel Cell Cooperation (Canada)
Fundersnot available
KeywordsCommercializationCharacterization (materials science)Automotive industryReliability (semiconductor)Reduction (mathematics)CathodeLayer (electronics)CatalysisKey (lock)NanotechnologyComputer scienceReliability engineeringMaterials scienceEngineeringProcess engineeringChemistryElectrical engineeringBusinessPhysicsAerospace engineeringComputer security

Abstract

fetched live from OpenAlex

This paper discusses key elements supporting continuing progress towards the achievement of the automotive PEMFC commercialization targets, in particular the reduction of total precious metal (PGM) content. An approach for PGM loading reduction without associated increase in mass transport loss is proposed, recent progress in advanced CL structural characterization/imaging is reviewed and the reliability of loss breakdown as guide for further performance improvement is discussed. A list of bulk and interface functionalities for the cathode catalyst layer is defined and the availability of measurement tools for the associated properties reviewed.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.274
Teacher spread0.227 · 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