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Record W2020013755 · doi:10.1016/j.otohns.2010.04.235

S113– eAGREE Training Tool

2010· article· en· W2020013755 on OpenAlexaff
Melissa Brouwers, Julie Makarski, Lisa Durocher

Bibliographic record

VenueOtolaryngology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Teaching and Evaluation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTraining (meteorology)Medical educationPsychologyComputer scienceMedicinePhysics

Abstract

fetched live from OpenAlex

Free accessAbstractFirst published online July 2010S113– eAGREE Training Tool: An electronic educational tool designed to improve a learner's performance, satisfaction, and self-efficacy with the AGREE IIMelissa C. Brouwers, PhD, Presenter, Julie Makarski, BSc, and Lisa D. Durocher, MScVolume 143, Issue 1_supplhttps://doi.org/10.1016/j.otohns.2010.04.235

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.043
GPT teacher head0.365
Teacher spread0.321 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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