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Record W2565686700 · doi:10.1123/ijatt.2015-0086

Investigating a Seven-Day Baseline While Establishing Healthy SCAT3 Symptom Frequency and Severity

2016· article· en· W2565686700 on OpenAlexaff
Michael J. Robinson, Danielle Mc Elhiney

Bibliographic record

VenueInternational Journal of Athletic Therapy & Training · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsWestern University
Fundersnot available
KeywordsChecklistObservational studyMedicineAthletesReliability (semiconductor)PopulationPsychologyClinical psychologyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Second only to a clinical exam, symptom checklists are used to aid in the evaluation of concussions. The validity of symptom checklists can become compromised by nonconcussed linked conditions that can vary day to day and are not taken into consideration during a baseline test. The purpose of this study was to assess the day-to-day reliability of the SCAT3 Symptom Evaluation and to determine the frequency and severity of the 22 symptoms in a nonconcussed, adult, athletic population. This study used a repeated-measure observational design and required participants to complete an online version of the SCAT3 Symptom Evaluation multiple times over a 7-day period. Moderate day-to-day reliability was found for the frequency and severity of symptoms and all of the 22 symptoms were reported by at least one participant. The results of the study suggest that the current practice of collecting the baseline symptoms once does not account for any day-to-day variation in symptoms and also demonstrates that all of the 22 symptoms listed on the SCAT3 Symptom Checklist can be present in nonconcussed, adult athletes.

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)0.004
metaresearch head score (Gemma)0.009
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.101
GPT teacher head0.356
Teacher spread0.255 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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Same venueInternational Journal of Athletic Therapy & TrainingSame topicTraumatic Brain Injury ResearchFrench-language works237,207