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Record W4398234867 · doi:10.25035/jsmahs.10.01.13

Athletic Trainers’ Knowledge and Perceived Ability of Recognizing and Treating Panic Attacks

2024· article· en· W4398234867 on OpenAlexaff
Caitlin Hill, Chyrsten Gessel, J. Tate

Bibliographic record

VenueJournal of Sports Medicine and Allied Health Sciences Official Journal of the Ohio Athletic Trainers Association · 2024
Typearticle
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsAthletic Edge Sports Medicine
Fundersnot available
KeywordsPanicPsychologyApplied psychologySocial psychologyAnxietyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE Mental health is a condition of mental wellness that enables people to manage life's stressors, develop their potential, study and work effectively, and give back to their communities. One mental health condition is anxiety. Anxiety is the expectation of a threat in the future. There are multiple subtypes of anxiety disorders, including panic disorder with or without agoraphobia, generalized anxiety disorder (GAD), social anxiety disorder (SAD), specific phobias, separation anxiety, and panic disorder. This study investigates the relationship between ATs' knowledge and their perceived ability to identify and treat panic attacks.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.056
GPT teacher head0.412
Teacher spread0.356 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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