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Record W4250221790 · doi:10.3148/cjdpr-2014-014

Abstracts from Dietetic Research Event – June 12–14, 2014

2014· article· en· W4250221790 on OpenAlexafffundvenueabout
Mary Elizabeth, Bénédicte Fontaine‐Bisson, A. Ong, Hope A. Weiler, Michael Wall, E Hamilton-Levitt, Rubina Dad, Stella S. Daskalopoulou, David Goltzman, Suzanne N. Morin, Julia MW Wong, Sonia Ruparell, Russell J. de Souza, Vanessa Ha, Joseph Beyene, Edward L. Giovannucci

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsMcMaster UniversityMcGill UniversitySt. Michael's HospitalOttawa HospitalOttawa Public HealthUniversity of TorontoMcGill University Health CentreUniversity of OttawaAlgonquin College
FundersCanadian Foundation for Dietetic Research
KeywordsPresentation (obstetrics)Medical educationEvent (particle physics)MedicineDiversity (politics)Work (physics)Foundation (evidence)Family medicinePolitical scienceEngineering

Abstract

fetched live from OpenAlex

Welcome to the nation's capital, Ottawa, Ontario host city of the 2014 Dietitians of Canada Annual Conference. The submissions for this year's Canadian Foundation for Dietetic Research event reflected the very high level of scientific quality and diversity of topics associated with Dietetic research in Canada. Through the support of Dietitians of Canada and the Canadian Foundation for Dietetic Research, the 2014 event was an educational and inspiring exchange of research and experience-sharing initiatives to help motivate conference attendees. The topics highlighted from this year's abstracts include Dietetic Practice and Education, Community-based Nutrition Education, Nutrition Health and Education, Vulnerable Groups and their Nutritional Needs, Clinical Research and Patient Services and much, much more. The research and experience-sharing work will provide new insights which can be applied to your work. Each presenter provided an 11 minute oral presentation (8 minutes for presenting and 3 minutes for questions). This allowed for meaningful interaction between the presenters and those attending the sessions. This year there were oral research presentations on each day of the conference: I urge you to use these presentations as an impetus to start your own research projects or to engage in conversations with your colleagues. This Research Event would not be possible without the commitment and dedication of many people. On behalf of Dietitians of Canada and the Canadian Foundation for Dietetic Research, I would like to extend a special thank you to the 2014 Abstracts Review Committee who represented research, clinical nutrition, community nutrition, education, food services and academics: Jennifer Brown (Registered Dietitian, The Ottawa Hospital Weight Management Clinic and Bariatric Surgery Program), Josée Bertrand (Acting Chief of Dietetics, The Ottawa Hospital), Marketa Graham (Public Health Dietitian, Ottawa Public Health Unit), Mahsa Jessri (PhD Candidate, Faculty of Medicine, University of Toronto), Mary Elizabeth Davies (Coordinator/Professor, Food and Nutrition Management, School of Hospitality & Tourism, Algonquin College), Dr. Bénédicte Fontaine-Bisson (Assistant Professor, Nutrition Sciences Program, University of Ottawa). I would also like to thank all of our moderators who took the time during the conference to keep our research presentation sessions on time. A special thank you to Shilpa Mukund and Isla Horvath at the Canadian Foundation for Dietetic Research for their guidance, patience, and support throughout the review process. I enjoyed interacting with many of you at the oral research presentations where we showcased the talents, efforts and important findings from our dietetic colleagues across our country. Marcia Cooper, PhD, RD Chair, 2014 Abstracts Review Committee Health Canada

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)0.008
metaresearch head score (Gemma)0.025
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: Other
Teacher disagreement score0.449
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.4490.224

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 head0.205
GPT teacher head0.514
Teacher spread0.309 · 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".

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Citations0
Published2014
Admission routes4
Has abstractyes

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