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Record W4411100663 · doi:10.1515/jnhpr-2022-040102

Abstracts of the 18th Annual Conference of the Natural Health Products Research Society of Canada: Food-derived NHPs in Health and Disease

2022· article· en· W4411100663 on OpenAlexaffabout
Pierre S. Haddad, Alain Doyen, Krista Coventry, Charles Ramassamy, Guy Rousseau, David H. St‐Pierre, Marleny D.A. Saldaña

Bibliographic record

VenueJournal of Natural Health Product Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsUniversité du Québec à MontréalInstitut National de la Recherche ScientifiqueUniversité LavalUniversity of AlbertaUniversité de Montréal
Fundersnot available
KeywordsDiseaseNatural (archaeology)Environmental healthGerontologyMedicinePolitical scienceGeographyPathologyArchaeology

Abstract

fetched live from OpenAlex

Abstract For their 18th Annual Conference, the Natural Health Product Research Society of Canada is proud to partner with the Institute for Nutrition and Functional Foods of Laval University in Quebec City to present a rich program of presentations on the theme of “Food-derived NHPs in Health and Disease”. Indeed, food provides humans with a plethora of natural compounds that help maintain health and mitigate disease. The conference abstracts cover state-of-the-art processing and quality approaches, novel food-derived ingredients, industry innovations as well as regulatory updates. The functionality of food-derived NHPs is covered through many angles including microbiota, nutrigenomics and pharmacology as well as in many disease states involving immunity, cancer, cognitive decline and mental health. Finally, a panel of experts addresses the role of NHPs in the practice of naturopathy.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score0.472

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0740.018

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 head0.069
GPT teacher head0.382
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreOther

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

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