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Record W6902120954 · doi:10.6084/m9.figshare.22600123

Additional file 1 of Prevalence of sensory impairments in home care and long-term care using interRAI data from across Canada

2023· article· en· W6902120954 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of TorontoUniversity of AlbertaUniversity of SaskatchewanUniversité de MontréalWilfrid Laurier University
Fundersnot available
KeywordsSensory lossHearing lossSensory systemNursing homesHome studyJob loss

Abstract

fetched live from OpenAlex

Additional file 1: Figure 1s. Hearing loss (HL) only trends over time by sex (all p-values <0.0001) in home care. Figure 2s. Vision loss (VL) only trends over time by sex (all p-values <0.0001) in home care. Figure 3s. Dual sensory loss (DSL) trends over time by sex (all p-values <0.0001) in home care. Figure 4s. Hearing loss (HL) only trends over time by sex in LTC. Figure 5s.. Vision loss (VL) only trends over time by sex (both p-values <0.0001) in LTC. Figure 6s. Dual sensory loss (DSL) trends over time by sex in LTC.

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)0.013
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: Empirical · Consensus signal: none
Teacher disagreement score0.372
Threshold uncertainty score0.895

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.009
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3720.024

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 head0.095
GPT teacher head0.363
Teacher spread0.268 · 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
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

Citations0
Published2023
Admission routes2
Has abstractyes

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