MétaCan
Menu
← Back to cohort
Record W6920860980 · doi:10.6084/m9.figshare.20484931

Additional file 1 of Prevalence and correlates of anxiety and depression in caregivers to assisted living residents during COVID-19: a cross-sectional study

2022· article· en· W6920860980 on OpenAlexaffabout

Bibliographic record

VenueFigshare · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of WaterlooMcMaster UniversityUniversity of OttawaInstitute for Clinical Evaluative SciencesUniversity of CalgaryUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsAnxietyDepression (economics)Observational studyMissing dataImputation (statistics)Confidence intervalMajor depressive disorderAnxiety disorder

Abstract

fetched live from OpenAlex

Additional file 1: Table S1. STROBE guidelines for reporting observational (cross-sectional) studies. Table S2. Descriptionof AL in Alberta and British Columbia, Canada. Table S3. Distribution of AL caregiver characteristics, overall and by missing responses for clinically significant anxiety disorder and depressive symptoms. Table S4. Adjusted risk ratios (95% confidence interval) for clinically significant anxiety disorder and depressive symptoms associated with AL caregiver characteristics [following Multiple Imputation of Missing Data].

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)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.638
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6380.040

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 head0.055
GPT teacher head0.379
Teacher spread0.323 · 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
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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFigshare→Same topicCOVID-19 and Mental Health→French-language works237,207→