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Record W4394476718 · doi:10.6084/m9.figshare.20341749

Supplemental Material for: The Risks of Cardiovascular Disease Following Weight Change in Adults with Diabetes: A Cohort Study and Meta-analysis

2022· dataset· en· W4394476718 on OpenAlexaboutno aff
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Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusCohortDiseaseCohort studyInternal medicineMeta-analysisGerontologyEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

This document contains supplemental material for the manuscript entitled " The Risks of Cardiovascular Disease Following Weight Change in Adults with Diabetes: A Cohort Study and Meta-analysis." This supplement contains 4 tables and 1 Figure. Table 1 showed Search strategy for PubMed, web of science and Embase. Table 2 was the results for sensitivity analysis by excluding patients with BMI<18.5kg/m2. Figure 1 showed summary of evidence search and selection. And table 4 was the results of Quality assessment. Table 3 showed the characteristics of included studies in the meta-analysis. Table 4 showed the Methodological quality assessment (risk of bias) of the included studies according to the Newcastle–Ottawa scales for cohort studies.

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)0.004
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.593
Threshold uncertainty score0.580

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.055
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0050.009
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5930.056

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 head0.088
GPT teacher head0.324
Teacher spread0.236 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2022
Admission routes1
Has abstractyes

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