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Record W4394321268 · doi:10.6084/m9.figshare.14447598

Metadata record for the article: Effect of Metformin versus Placebo on Metabolic Factors in the MA.32 Randomized Adjuvant Breast Cancer Trial

2021· dataset· en· W4394321268 on OpenAlexaboutno aff
Pamela J. Goodwin, Ryan J.O. Dowling, Marguerite Ennis, Bingshu E. Chen, Wendy R. Parulekar, Lois E. Shepherd, Margot J. Burnell, R Vandermeer, Andrea Molckovsky, Anagha Gurjal, Karen A. Gelmon, Jennifer A. Ligibel, Dawn L. Hershman, Ingrid A. Mayer, Timothy J. Whelan, Timothy J. Hobday, Priya Rastogi, Manuela Rabaglio, Julie Lemieux, Alistair M. Thompson, Daniel Rea, Vuk Stambolic

Bibliographic record

VenueFigshare · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsMetforminMetadataPlaceboRandomized controlled trialMedicineAdjuvantBreast cancerOncologyInternal medicineCancerAlternative medicineWorld Wide WebComputer sciencePathology

Abstract

fetched live from OpenAlex

Summary This metadata record provides details of the data supporting the claims of the related article: “Effect of Metformin versus Placebo on Metabolic Factors in the MA.32 Randomized Adjuvant Breast Cancer Trial”. The related study examined metformin impact on metabolic factors in non-diabetic subjects to determine whether this impact varies by baseline BMI, insulin and rs11212617 SNP in CCTG MA.32, a double-blind placebo controlled randomised adjuvant breast cancer (BC) trial. Type of data: single-nucleotide polymorphism (SNP); clinical data Subject of data: Homo sapiens Sample size: 2915 Population characteristics: See Table 1 of the related article Trial registration number: http://clinicaltrials.gov/show/NCT01101438 Data access The SNP data are openly available as part of this figshare metadata record in the file ‘MA32_snp_data.csv’. The primary efficacy analysis will be available from the Canadian Cancer Trials Group (Kingston, Ontario) after the results of the analysis have been published. These data will be uploaded to the NCI data archive website: https://nctn-data-archive.nci.nih.gov/view-trials and will be searchable via NCT trial number NCT01101438. As of April 2021, the group is working towards this publication. Further details can be requested from the corresponding author. The clinical data are not publicly available for the following reason: data contain information that could compromise research participant privacy. Corresponding author(s) for this study Dr. Pamela J. Goodwin, Mount Sinai Hospital, 1085-600 University Avenue, Toronto, Ontario M5G 1X4. Tel: 416-586-8211. Fax: 416-586-3199. Email: Pamela.Goodwin@sinaihealthsystem.ca. Study approval The study protocol was approved by institutional review boards of participating institutions, including the NCI (US) Central Institutional Review Board and Mount Sinai Hospital (Ontario Cancer Research Ethics Board).

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)0.009
metaresearch head score (Gemma)0.089
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 score0.794
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.089
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.010
Science and technology studies0.0020.001
Scholarly communication0.0060.005
Open science0.0030.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.7940.275

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 head0.033
GPT teacher head0.313
Teacher spread0.280 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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