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Record W4254887624 · doi:10.3148/cjdpr-2015-026

Abstracts from Dietetic Research Event – June 04–06, 2015

2015· article· en· W4254887624 on OpenAlexafffundvenueabout
Melanie Morris

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsAthabasca UniversityHospital for Sick ChildrenSickKids FoundationUniversity of TorontoHolland Bloorview Kids Rehabilitation HospitalWestern University
FundersSchulich School of Medicine and DentistryCanadian Foundation for Dietetic ResearchAlberta Health ServicesSchulich School of Medicine and Dentistry, Western UniversityBrescia University CollegeChildren's Health Research Institute
KeywordsMedicinePresentation (obstetrics)Medical educationDiversity (politics)Nutrition EducationFoundation (evidence)Event (particle physics)Family medicineWeight managementService (business)NursingGerontologyObesityWeight lossPolitical science

Abstract

fetched live from OpenAlex

Bonjour! Welcome to Québec City, the capital of the province of Québec. This historic city was the host of the 2015 Dietitians of Canada Annual Conference. The submissions for this year's Canadian Foundation for Dietetic Research event represented the diversity of dietetic research conducted within Canada. Through the support of Dietitians of Canada and the Canadian Foundation for Dietetic Research, the 2015 event was both an exciting and informative exchange of research and experience-sharing efforts that inspired attendees. The topics highlighted from this year's abstracts include Community-Based Nutritional Care, Wellness and Public Health–Children, Determinants of Food Choice, Dietary Intake, Nutrition Health and Education, Dietetic Practice and Education, Clinical Research and Patient Service, Nutrition Social Media and the Web, Nutrition Labelling and Patient Services. 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 we had over 50 presentations. These presentations offer the newest insights into important research findings that you may be able to apply to your own practice. 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 2015 Abstracts Review Committee who represented research, clinical nutrition, community nutrition, and education: Jennifer Brown (Registered Dietitian, The Ottawa Hospital Weight Management Clinic and Bariatric Surgery Program), Marketa Graham (Public Health Dietitian, Ottawa Public Health Unit), Mahsa Jessri (PhD Candidate, Faculty of Medicine, University of Toronto), Hélène Lowell (Nutrition Advisor, Health Canada), and Joseph Murphy (Professional Practice Co-ordinator, The Ottawa Hospital). 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 Greg Sarney at the Canadian Foundation for Dietetic Research for their assistance, patience, and support throughout the review process. I enjoyed interacting with many of you at the oral research presentations where we highlighted the findings from our dietetic colleagues across our country. Marcia Cooper, PhD, RD Chair, 2015 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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.377
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.000
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.6230.381

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 head0.360
GPT teacher head0.558
Teacher spread0.198 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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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Citations1
Published2015
Admission routes4
Has abstractyes

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