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Record W6963047689 · doi:10.17632/9jhhttr8fz.1

Punjabi translation of the Western Ontario Rotator Cuff Index and to evaluate its adaptation, validity and reliability

2025· dataset· en· W6963047689 on OpenAlexaboutno aff

Bibliographic record

VenueMendeley Data · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRotator cuffReliability (semiconductor)Delphi methodUsabilityDelphiIntraclass correlationIndex (typography)Content validityQuality of life (healthcare)

Abstract

fetched live from OpenAlex

The Western Ontario Rotator Cuff Index (WORC) is a self-assessment tool developed by Kirkley et al. (2003) to measure disease-specific quality of life in patients with symptomatic rotator cuff disorders. t was originally developed in English and then translated in different languages to measures its usability in different cultures. The study aims to translate and culturally adapt the Western Ontario Rotator Cuff Index (WORC) into Punjabi and assess its validity and reliability. Following Beaton’s Guidelines, the translation process included forward and backward translation by two translators, with approval from the original developer. Content validation was conducted using the Delphi method with 10 field experts having over five years of experience. Cultural adaptation involved 30 outpatient participants who provided feedback on scale clarity. Concurrent validation compared P-WORC scores with WORC and DASH, while reliability testing was performed with 51 patients to ensure consistency and accuracy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.295
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.340
Teacher spread0.223 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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