Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
VenueClinical Nutrition · 2018
Typereview
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of TorontoUniversity of CalgaryUniversity of SaskatchewanSt. Michael's Hospital
FundersNovo Nordisk CanadaInstituto de Salud Carlos IIIAlmond Board of CaliforniaCanadian Agri-Food Policy InstituteInstituto DanoneAmgen CanadaNovo NordiskCanada Research ChairsSanofiCanadian Society of Endocrinology and MetabolismPfizer CanadaOntario Ministry of Research, Innovation and ScienceCanada Foundation for InnovationHospital for Sick ChildrenAdvanced Foods and Materials NetworkGriffin HospitalNational Dried Fruit Trade AssociationCanola Council of CanadaKellogg'sAlpro FoundationInternational Nut and Dried Fruit CouncilPhysicians' Services Incorporated FoundationPeanut InstituteCanadian Nutrition SocietyUnileverArizona State UniversityDanone Institute of CanadaAstraZeneca CanadaCanadian Institutes of Health ResearchCanadian Diabetes AssociationMinisterio de Ciencia y TecnologíaOntario Research FoundationPepsiCoCognitive Neuroscience SocietyInstitute of Nutrition, Metabolism and DiabetesCalifornia Strawberry CommissionRocheGeneral MillsEuropean CommissionBanting and Best Diabetes Centre, University of TorontoSt. Michael's Hospital FoundationMerck Sharp and DohmeFlax Council of CanadaNovartisSaskatchewan Pulse GrowersAmgenInstitute of Food TechnologistsAbbott LaboratoriesBayerDepartament de Salut, Generalitat de CatalunyaCoca-ColaPfizerEli Lilly and CompanyJohnson and JohnsonMeso Scale DiagnosticsGovernment of Canada
KeywordsMedicineMeta-analysisRandomized controlled trialDiabetes mellitusType 2 diabetesInternal medicineEndocrinology
Abstract
fetched live from OpenAlexNo abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
metaresearch head score (Codex)0.041
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMetaresearch, Meta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.718
Threshold uncertainty score1.000
Codex and Gemma teacher scores by category
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.
Teacher spread0.321 · 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
