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Developments of Fuel Cell and Hydrogen Technology at NRC's Institute for Fuel Cell Innovation

2007· article· en· W2050028061 on OpenAlexaffabout
Dave Ghosh, Shao Hong Wu

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCommercializationFuel cellsMandateGovernment (linguistics)Proton exchange membrane fuel cellSolid oxide fuel cellBusinessEngineering managementResearch councilEngineeringPolitical scienceMarketing

Abstract

fetched live from OpenAlex

National Research Council (NRC) as the premier research and development organization within the government of Canada has the mandate of providing vital scientific and technological services to research and industrial communities. The NRC Institute for Fuel Cell Innovation (IFCI) is leading NRC’s National Fuel Cell Program and is working closely with academic, government, and industrial organizations to support fuel cell cluster in Vancouver and across Canada and to fulfill the innovation needs of Canadian fuel cell companies. The key programs at IFCI include: Proton Exchange Membrane Fuel Cells (PEMFC), Solid Oxide Fuel Cells (SOFC), Hydrogen generation and infrastructure, and technology demonstration. NRC-IFCI’s impact on the fuel cell industry can be seen through the development and transfer of targeted and collaborative research projects addressing strategic and current technical gaps and providing infrastructure for research, development and demonstration. IFCI has been a catalyst in the coordination of industry’s responses to current commercialization barriers. This paper presents the latest research and development activities as well as demonstrations at NRC-IFCI.

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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.211
Teacher spread0.203 · 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 teacher head, 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

Citations3
Published2007
Admission routes2
Has abstractyes

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