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Record W3048358429 · doi:10.4038/cmj.v65i1-2.9134

Cross-cultural adaptation and validation of the Leibowitz Social Anxiety Scale (LSAS-SR) Sinhala Version

2020· article· en· W3048358429 on OpenAlexaff
Aruni Hapangama, Lalith A. Kuruppuarachch, Ransirini De Silva, Ananda R. Wickremasinghe, Arun Ravindran, Shehan Williams

Bibliographic record

VenueCeylon Medical Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineAdaptation (eye)Scale (ratio)Social anxietyCross-culturalAnxietyClinical psychologyPsychiatryOpticsCartographyAnthropology

Abstract

fetched live from OpenAlex

Ceylon Medical Journal (CMJ) is a peer-reviewed, open access journal published quarterly by the Sri Lanka Medical Association in the last week of March, June, September and December each year. The mission of the CMJ is to promote the science and art of medicine and betterment of public health. The Journal publishes original papers and commentaries which have relevance to medicine and allied sciences. The CMJ is committed to maintaining and conforming to the editorial and ethical standards recommended by the International Committee of Medical Journal Editors.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.039
GPT teacher head0.392
Teacher spread0.353 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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