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Record W1981554717 · doi:10.3138/ptc.2012-42

An Example of End-Digit Preference in Physiotherapy Practice

2013· article· en· W1981554717 on OpenAlexaffvenue
Paul W. Stratford, Amy Wainwright, Deborah Kennedy

Bibliographic record

VenuePhysiotherapy Canada · 2013
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoMcMaster University
Fundersnot available
KeywordsNumerical digitGoniometerRange of motionPhysical therapyPreferencePhysical medicine and rehabilitationTotal knee replacementMedicinePsychologySurgeryMathematicsArithmeticStatistics

Abstract

fetched live from OpenAlex

PURPOSE: Standardizing and improving the validity of range of motion (ROM) measurements is of clinical relevance to physiotherapists. The purpose of this study was to assess whether end-digit preference exists in the measurement of knee ROM in people after knee replacement. METHOD: Following total knee replacement, 100 people underwent active-assisted knee ROM measurements using a goniometer calibrated in 1° increments. RESULTS: The data showed strong end-digit preferences for 0s and 5s (p<0.001). CONCLUSIONS: End-digit preference does exist in the measurement of knee ROM. This has the potential to influence both the validity of ROM measurements and clinical decisions.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.293
Teacher spread0.271 · 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.

Study designObservational
DomainReporting
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
Published2013
Admission routes2
Has abstractyes

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