MétaCan
Menu
Back to cohort
Record W1996700008 · doi:10.1007/s13679-013-0072-9

Obesity, Complexity, and the Role of the Health System

2013· review· en· W1996700008 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCurrent Obesity Reports · 2013
Typereview
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsSimon Fraser University
FundersSFU Community Trust Endowment FundCanadian Institutes of Health ResearchSimon Fraser University
KeywordsObesityHealthcare systemHealth careSystems thinkingMedicinePsychologyRisk analysis (engineering)Computer sciencePolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

As obesity continues to increase throughout the world, there is still no well-defined solution to the issue. Reducing obesity poses a significant challenge for the health care system because it is a complex problem with numerous interconnections and elements. The complexity of obesity challenges traditional primary care practices that have been structured to address simple or less complicated conditions. Systems thinking provides a way forward for clinicians that are discouraged or overwhelmed by the complexity of obesity. At any given level, individuals matter and system functioning is optimized when our capacity is well matched to the complexity of our tasks. Shifting paradigms around the causes of obesity is essential for creating a health care system that promotes innovative and collaborative practice for healthcare practitioners and individuals dealing with obesity.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.198
GPT teacher head0.487
Teacher spread0.288 · 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