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Record W2400725293 · doi:10.1037/0003-066x.63.3.202

Undereating or eliminating overeating?

2008· article· en· W2400725293 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.

Bibliographic record

VenueAmerican Psychologist · 2008
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOvereatingPsychologyMedicineObesityInternal medicine

Abstract

fetched live from OpenAlex

Comments on an article titled Medicare's Search for Effective Obesity Treatments: Diets Are Not the Answer, by Mann et al. The current authors state that on the basis of their review of studies of long-term outcomes of calorie-restricting diets, Mann et al. concluded that dieting does not lead to lasting weight loss. Although this conclusion is hardly new--see Stunkard's (1975, p. 196) famous verdict: "Of those who do lose weight, most will regain it"--it is still valuable in view of recent more optimistic claims that "the success rate for long-term weight loss is closer to 20%" (Fletcher, 2003, p. 822). Mann et al.'s (2007) indictment of dieting as a treatment for obesity seems warranted, but that indictment ought not to extend to efforts to eliminate overeating. No one denies the benefits of exercise, for which Mann et al. (2007) are strong advocates. An exercise regimen, however, does not address overeating tendencies and therefore may be ineffective or even counterproductive (insofar as exercise may "justify" overeating). Further, we must acknowledge that exercise may improve health without necessarily lowering weight. Muscle weighs more than fat does, so losing fat is not necessarily the same as losing weight.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.366
Threshold uncertainty score0.480

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.074
GPT teacher head0.375
Teacher spread0.302 · 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