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Record W2033165572 · doi:10.3148/63.3.2002.130

<i>Weight Management In Childhood</i>Canadian Dietitians’ Practices

2002· article· en· W2033165572 on OpenAlexaffvenueabout
Shalene Wray, Ryna Levy-Milne

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2002
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOverweightMedicineFamily medicineIntervention (counseling)Weight managementBody mass indexPopulationBest practiceNursingEnvironmental health

Abstract

fetched live from OpenAlex

Canadian dietitians specializing in pediatric practice were surveyed to provide a preliminary profile of the strategies they use to manage overweight youth. The survey was mailed to 298 dietitians belonging to the Dietitians of Canada's (DC) Pediatric Nutrition and Consulting Dietitians' Networks and to the head dietitians in Canadian pediatric hospitals across the country. It was also posted on the DC website and sent by electronic mail. Of the 164 respondents, 65 reported that they provide an intervention program to overweight youth. Growth charts, ideal body weight, and body mass index were mostly used to assess and monitor overweight. However, about 20% of the respondents did not define overweight in their client population. The majority of the clients were girls aged seven to 18. Most respondents used the healthful lifestyle approach via one-on-one consultation, included parents and collaborated with two or more health professionals for the management of these children. As the discussion on best practices for the prevention and treatment of overweight youth continues, we need further evidence to determine what strategies, if any, support positive outcomes in this group.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.069
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.357
Teacher spread0.294 · 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

Citations1
Published2002
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Dietetic Practice and ResearchSame topicObesity, Physical Activity, DietFrench-language works237,207