MétaCan
Menu
Back to cohort
Record W7071706608

UND professor appointed co-editor of major book series on sports medicine

2014· article· en· W7071706608 on OpenAlexaboutno aff

Bibliographic record

VenueUND Scholarly Commons (University of North Dakota) · 2014
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsnot available
Fundersnot available
KeywordsKinesiologyInterimRecreationPublic healthPhysical educationSports medicineSports scienceSport management
DOInot available

Abstract

fetched live from OpenAlex

Dennis Caine, professor and chair in the University of North Dakota's Department of Kinesiology & Public Health Education, part of the College of Education & Human Development (CEHD), was named series co-editor for the long-standing Karger Publisher's book series, titled Medicine and Sport Science on Jan. 1. Caine also currently serves on editorial review boards for the British Journal of Sport Medicine (associate editor), Clinical Journal of Sport Medicine, and Research in Sports Medicine: An International Journal. Prior to coming to UND, Caine was a professor in the Department of Physical Education, Health and Recreation at Western Washington University in Bellingham, from 1992-2007. He began his career as a physical education teacher in Canada and with the Canadian Department of National Defense in Germany. Caine's research interests involve the epidemiology of injury in sport and recreation activities, injury and growth and the effects of intensive training on growth. Within the Department of Kinesiology & Public Health Education, Caine teaches Epidemiology in Public Health, Applied Motor Development, Motor Development and Physical Activity Epidemiology. Caine is a former interim dean of the CEHD.

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)0.001
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0460.041

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 head0.013
GPT teacher head0.258
Teacher spread0.245 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueUND Scholarly Commons (University of North Dakota)Same topicSports injuries and preventionFrench-language works237,207