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Record W6967427296 · doi:10.5281/zenodo.10371746

Trousse d'activités ludiques favorisant le savoir-être des stagiaires

2021· other· fr· W6967427296 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typeother
Languagefr
Field
Topic
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsContext (archaeology)Manpower planningCenter (category theory)

Abstract

Trousse destinée aux superviseurs de stage qui souhaitent accorder une place importante au savoir-être dans le contexte de la supervision. La trousse comprend sept activités ludiques, les scénarios pédagogiques et le matériel nécessaire à la mise en œuvre des activités dans le cadre des supervisions collectives de stages. Des fiches explicatives présentent les modèles et les principes pédagogiques sous-jacents aux activités de la trousse. Un carnet de réflexion comprend des questions supplémentaires qui favorisent la réflexion du stagiaire.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: french · design weight: 1554.47 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: other
about Canada: no
confidence: high

Toolkit of playful activities for internship supervisors to develop trainees' professional soft skills; a teaching resource for practicum supervision, not about the research workforce or research practice.

GPT-5.6 (high)OUT
genre: infrastructure/announcement
about Canada: no
confidence: high

The record is an educational activity toolkit for internship supervisors, not a study of research.

Grok 4.5OUT
genre: other
about Canada: no
confidence: high

Pedagogical activity kit for internship soft skills supervision; education practice resource, not research about research.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0300.004

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 head0.055
GPT teacher head0.263
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)French-language works237,207