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Record W47110577

National Research Council – Institute for Fuel Cell Innovation: Proposed process for evaluating collaborative projects

2007· dissertation· en· W47110577 on OpenAlexfundaboutno aff
Thomas Peter Hummel

Bibliographic record

VenueSummit (Simon Fraser University) · 2007
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategies and Innovation
Canadian institutionsnot available
FundersSimon Fraser University
KeywordsResearch councilEngineering managementProcess (computing)Fuel cellsEngineeringPolitical scienceProcess managementManufacturing engineeringBusinessComputer scienceChemical engineering
DOInot available

Abstract

fetched live from OpenAlex

The National Research Council Institute for Fuel Cell Innovation (NRC – IFCI) is a government institution charged with aiding the development of the fuel cell industry in Canada. One way in which this is accomplished is for the NRC – IFCI to engage in collaborative partnerships with other organizations. The current process for evaluating and selecting these projects relies heavily on the knowledge and intuition of a few key individuals, and lacks the structure to align organizational and project goals. This project will propose changes which will address these issues. It will also make recommendations for further improvement. The proposed changes are intended to start a dialogue. The impact will be greatly enhanced by contributions from the existing agents of the NRC – IFCI who are currently making decisions on collaborative projects.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.764
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.010
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0010.000
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 head0.155
GPT teacher head0.351
Teacher spread0.196 · 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.

Study designNot applicable
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

Citations0
Published2007
Admission routes2
Has abstractyes

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