MétaCan
Menu
Back to cohort
Record W2233294514 · doi:10.3148/cjdpr-2015-002

Promoting Plant-based Diets

2015· editorial· en· W2233294514 on OpenAlexvenueno aff
Dawna Royall

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2015
Typeeditorial
Languageen
FieldAgricultural and Biological Sciences
TopicAgroforestry and silvopastoral systems
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthBusinessMedicine

Abstract

fetched live from OpenAlex

PromotingPlant-based Diets R ecently we were contacted by a librarian compiling a bibliography on vegetarian diets, who identified that the term "plant-based diet" first appeared in a 1975 article published in the Journal of the Canadian Dietetic Association.This article can be accessed here.In this article, the authors developed a vegetarian food guide based on 4 food groups: breads and cereals, vegetable protein foods, milk and eggs, and fruits and vegetables [1].Student volunteers used the guide to plan a 1-day menu; however, only 1 of 13 student menus met all of the nutrient requirements, primarily due to a failure to rely on vegetable protein foods to meet protein requirements.The authors subsequently modified the instructions and explanations for using the food guide into a 13-page booklet.Forty years later, in this issue of the Journal, 2 articles focus on the benefits and challenges of consuming plant-based diets.Phillips et al. identify perceived benefits and barriers to lentil consumption among caregivers in a school setting.Luhovyy et al. report the results of a short-term study examining the metabolic effects of ready-to-eat legumes in overweight/obese adults.The results of these studies encourage us to consume more legumes and to develop targeted health promotion strategies to promote legume consumption.This year's nutrition month slogan, "Eating 9 to 5!" is inspiring Canadians to eat better at work.Challenged with rushed mornings, the mid-day slump, and commuter cravings?The Nutrition Month campaign is packed with daily tips to promote a healthy nutrition environment during these challenging times (www.nutritionmonth2015.ca).Take advantage of this opportunity to promote a healthier environment in your workplace.I would like to take this opportunity to formally acknowledge and extend my sincere appreciation to those individuals in 2014 who volunteered their time and expertise to review submissions to the Journal (see the list of reviewers for 2014).The volunteer peer review process maintains the high quality of published articles relevant to dietitians.

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)0.003
metaresearch head score (Gemma)0.007
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0070.002

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 head0.084
GPT teacher head0.345
Teacher spread0.261 · 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
GenreEditorial

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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Dietetic Practice and ResearchSame topicAgroforestry and silvopastoral systemsFrench-language works237,207