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Record W6891719329 · doi:10.4224/21277154

Audit of the Industrial Research Assistance Program in the interim operating environment: June 2015

2015· report· en· W6891719329 on OpenAlexafffundabout

Bibliographic record

Venuenot available
Typereport
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsNational Research Council Canada
FundersGovernment of Canada
KeywordsInterimAuditFiscal yearAudit planInformation technology auditJoint auditInternal auditFinancial Audit

Abstract

fetched live from OpenAlex

This audit report presents the findings of the National Research Council Canada’s (NRC) Audit of the Industrial Research Assistance Program (IRAP) in the Interim Operating Environment (IOE). The objective of the audit was to provide just-in-time independent assurance to NRC Senior Management that controls remained effective in the Interim Operating Environment (IOE) to allow NRC to make necessary corrections before fiscal year-end.

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)0.038
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.091
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0030.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.005

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 head0.660
GPT teacher head0.576
Teacher spread0.084 · 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.

Study designObservational
DomainEvaluation
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
Published2015
Admission routes3
Has abstractyes

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