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Record W4400040967 · doi:10.58931/cwht.2024.1210

Consideration of Use of Semaglutide and Tirzepatide Prior to Pregnancy

2024· article· en· W4400040967 on OpenAlexaff
Alyse S. Goldberg

Bibliographic record

VenueCanadian Women s Health Today · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSemaglutidePregnancyObstetricsMedicineBiologyEndocrinologyDiabetes mellitus

Abstract

fetched live from OpenAlex

In reproductive-age females with elevated body mass index (BMI), weight loss is often recommended independent of their reproductive and family planning goals. However, it is clear that lifestyle methods for losing weight often fall short of achieving and maintaining weight loss. As approaches to addressing obesity and weight optimization evolve beyond the simplistic notion of “eat less and move more,” there has been a growing acceptance of weight loss medications as part of comprehensive weight management strategies. It should also be noted that health optimization cannot be solely attributed to reducing BMI or kilograms of body weight. The objective of this paper is not to contribute to the well-established weight stigma in medicine, but rather to highlight a thoughtful approach to the use of weight loss medication in a cohort where the prevalence is expected to rise independent of the indication.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.286
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2024
Admission routes1
Has abstractyes

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