La science à l'oeuvre pour le Canada : une stratégie pour le Conseil national de recherches : 2006-2011
Bibliographic record
Abstract
Pendant près d’un siècle, le Conseil national de recherches (CNRC) a excellé sur les scènes nationale et internationale en recentrant continuellement ses activités pour mieux répondre aux nouvelles priorités et aux nouveaux défis nationaux. Aujourd’hui, plus que jamais, le CNRC est en mesure de stimuler la croissance d’industries de classe mondiale axées sur la science et la technologie, de soutenir des grappes de technologies innovatrices dans toutes les régions du pays, et de contribuer à des initiatives de recherche et développement multidisciplinaires et de grande envergure partout au Canada. Notre stratégie mise sur toutes ces possibilités. Jamais le but du CNRC n’a été aussi bien défini et le besoin d’évolution plus pressant. Fort de sa nouvelle stratégie et appuyé par 90 années de fiers services au bénéfice du pays, le CNRC s’engage avec confiance vers un avenir prometteur.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".