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Record W1014867827

"Body Contouring After Massive Weight Loss," edited by A. Aly.

2006· article· en· W1014867827 on OpenAlexaboutno aff
Vivian C. McAlister

Bibliographic record

VenueScholarship@Western (Western University) · 2006
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWeight lossBody contouringMedicineInternal medicineObesity
DOInot available

Abstract

fetched live from OpenAlex

Nowhere is the failure of the health care system, as currently managed, more evident than in the surgical care of obesity. A marked contrast has emerged between surgery in the United States and Canada for these patients. It is not clear whether the reluctance to supply surgical services in Canada is due to a bias in favour of “more deserving” patients or whether the considerably higher rate of obesity surgery in the US is due to the excesses of private enterprise. Governments have acknowledged that an element of the former proposition is true by referring obese patients to centres in the US. This practice, which appears to be a measure to keep the peace with failing managements of the superhospitals, undermines the whole foundation of surgical practice in Canada. For the first time, surgeons have not acknowledged a responsibility for the care of a whole sector of society. Not only do considerable resources follow these patients over the border, but an opportunity to refine laparoscopic surgical skills is being wasted.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.035
GPT teacher head0.296
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 teacher head, not a consensus.

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

Citations0
Published2006
Admission routes1
Has abstractyes

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