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Record W995127483 · doi:10.1520/stp15236s

Spinal and Head Injuries in Ice Hockey - A Three Decade Perspective

2000· book-chapter· en· W995127483 on OpenAlexaffabout
CH Tator, JD Carson, VE Edmonds

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsIce hockeyHead (geology)Perspective (graphical)AeronauticsEngineeringGeographyPsychologyPhysical medicine and rehabilitationGeologyMedicineComputer scienceArtificial intelligencePaleontology

Abstract

fetched live from OpenAlex

Over the past three decades ice hockey has changed, particularly the severity of the injuries. Our objectives in this study are to give a historical overview and examine the nature and incidence of major spinal and head injuries sustained while playing ice hockey. Using a retrospective review of questionnaires returned by physicians, we have previously reported 241 cases of fracture or dislocation of the spine, up to the end of 1993. Between 1982 and 1993 an average of 16.8 ice hockey related major spinal injuries were reported each year, from Canada primarily. Most of these injuries occurred to the cervical spine of players 16 to 20 years of age who were playing in supervised games. Our latest study, now nearing completion, will add more cases to our registry, up to the end of 1996. These include a recent dramatic increase in spinal fractures reported by USA Hockey. In addition, we have included concussions in our latest survey because a lack of consistent adherence to hockey rules and to a respectful attitude may impact upon both spinal and head injury and the etiology may be overlapping in some cases.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.326
Teacher spread0.302 · 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 designObservational
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".

Quick stats

Citations5
Published2000
Admission routes2
Has abstractyes

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