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Record W4210596990 · doi:10.2196/34656

Serious Games Without Screens. Comment on “Involvement of End Users in the Development of Serious Games for Health Care Professions Education: Systematic Descriptive Review”

2022· article· en· W4210596990 on OpenAlexaffvenue
Michael Cosimini, Bjorn Watsjold, Teresa M. Chan

Bibliographic record

VenueJMIR Serious Games · 2022
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDescriptive researchPsychologyHealth careMedical educationHealth professionsComputer scienceMedicineSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.046
metaresearch head score (Gemma)0.256
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.046
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.256
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0030.008
Open science0.0050.005
Research integrity0.0270.020
Insufficient payload (model declined to judge)0.0220.012

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 head0.045
GPT teacher head0.383
Teacher spread0.338 · 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
GenreCommentary

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

Citations10
Published2022
Admission routes2
Has abstractyes

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