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Record W4382786309 · doi:10.1701/4062.40461

Le evidenze della ricerca sull’obesità: tradurle nella clinica e in strategie di sanità pubblica

2023· article· en· W4382786309 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

VenueRecenti Progressi in Medicina · 2023
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsCanadian Obesity Network
Fundersnot available
KeywordsMultidisciplinary approachObesityPublic healthMedicineContinuing medical educationDiseaseNarrativeHealth careMedical educationDisseminationContinuing educationNursingPolitical sciencePathology

Abstract

fetched live from OpenAlex

L’obesità è una malattia complessa che deriva dall’interazione di fattori genetici, psicologici e ambientali. Sfortunatamente, una carenza significativa nell’approccio generale all’obesità è l’incapacità di tradurre in una pratica virtuosa i risultati della ricerca. Sono molti gli ostacoli da superare per mettere in pratica le moderne evidenze scientifiche: dalla cultura medica all’organizzazione del sistema sanitario nazionale maggiormente centrata sul trattamento delle patologie acute, per finire con l’attuale narrazione dell’obesità come problema estetico e non sanitario. È assolutamente necessario per evitare una assurda penalizzazione che l’obesità venga inserita al più presto nell’elenco delle malattie croniche e, di conseguenza, nel piano nazionale della cronicità. Solo allora si potranno mettere in campo programmi di traslazione finalizzati a diffondere le competenze e le conoscenze tra gli operatori della rete e a promuovere l’interdisciplinarietà in ambito medico attraverso la formazione di team specialistici dedicati.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.333
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.003

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 head0.155
GPT teacher head0.505
Teacher spread0.350 · 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