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Record W4391888693 · doi:10.1111/edt.12931

The International Association of Dental Traumatology (<scp>IADT</scp>) and the Academy for Sports Dentistry (<scp>ASD</scp>) guidelines for prevention of traumatic dental injuries: Part 10: First aid education

2024· article· en· W4391888693 on OpenAlexaff
Nitesh Tewari, Paul V. Abbott, Anne C. O’Connell, Stephen C. Mills, Hans Stasiuk, Mark Roettger, Liran Levin

Bibliographic record

VenueDental Traumatology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsUniversity of AlbertaUniversity of Manitoba
Fundersnot available
KeywordsTraumatologyDental traumaMedicineDentistrySports injuryOccupational safety and healthPoison controlInjury preventionHuman factors and ergonomicsSuicide preventionMedical emergencyPhysical therapyOrthopedic surgeryPsychiatryPathology

Abstract

fetched live from OpenAlex

The Guidelines for Prevention of Traumatic Dental Injuries were reviewed and approved by the Board of Directors of the International Association of Dental Traumatology (IADT) and the Academy for Sports Dentistry (ASD).

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)0.014
metaresearch head score (Gemma)0.039
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: Methods · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0190.010

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 head0.079
GPT teacher head0.443
Teacher spread0.364 · 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
GenreMethods

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

Citations21
Published2024
Admission routes1
Has abstractyes

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