MétaCan
Menu
Back to cohort
Record W2944799710 · doi:10.3148/cjdpr-2019-013

Provincial Differences in Long-Term Care Menu Variety and Food Intake for Residents who Consume a Regular Texture

2019· article· en· W2944799710 on OpenAlexafffundvenueabout
Christine Lagacé, Natalie Carrier, Lita Villalón, Christina Lengyel, Susan E. Slaughter, Jill Morrison, Heather Keller

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2019
Typearticle
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsResearch Institute for AgingUniversity of WaterlooUniversity of AlbertaUniversity of ManitobaUniversité de Moncton
FundersCanadian Institutes of Health Research
KeywordsMedicineVariety (cybernetics)Food intakeEnvironmental healthFood groupHealthy foodGerontologyDemographyFood scienceMathematicsBiologyStatistics

Abstract

fetched live from OpenAlex

This study is the first in Canada to assess LTC menu variety. Although there was variability between provinces in menu variety, this was not associated with resident diet quality or intake.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.079
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.374
Teacher spread0.322 · 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

Citations4
Published2019
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Dietetic Practice and ResearchSame topicNutrition, Health and Food BehaviorFrench-language works237,207