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Record W2783680796 · doi:10.24095/hpcdp.38.1.03

Healthy food procurement and nutrition standards in public facilities: evidence synthesis and consensus policy recommendations

2018· review· en· W2783680796 on OpenAlexafffundvenueabout
Kim D. Raine, Kayla Atkey, Dana Lee Olstad, Alexa R. Ferdinands, Dominique Beaulieu, Susan Buhler, Norm R.C. Campbell, Brian Cook, Mary R. L’Abbé, Ashley Lederer, David L. Mowat, Joshna Maharaj, Candace I. J. Nykiforuk, Jacob Shelley

Bibliographic record

VenueHealth Promotion and Chronic Disease Prevention in Canada · 2018
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsWestern UniversityUniversity of TorontoToronto Public HealthCanadian Partnership Against CancerLibin Cardiovascular Institute of AlbertaAlberta Health ServicesUniversité du Québec à RimouskiUniversity of CalgaryUniversity of Alberta
FundersHealth CanadaPartenariat Canadien Contre Le Cancer
KeywordsProcurementContext (archaeology)BusinessPublic healthPublic relationsPolitical scienceEnvironmental healthMedicineMarketingNursing

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.191
metaresearch head score (Gemma)0.336
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.191
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1910.336
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0250.028
Science and technology studies0.0070.007
Scholarly communication0.0150.008
Open science0.0120.009
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0120.002

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 head0.138
GPT teacher head0.407
Teacher spread0.269 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations35
Published2018
Admission routes4
Has abstractyes

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