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Record W2977359292

Maternal body mass index, gestational weight gain, and the risk of overweight and obesity across childhood: An individual participant data meta-analysis

2019· article· en· W2977359292 on OpenAlexaff
Ellis Voerman, Susana Santos, Bernadeta Patro-Gołąb, Pilar Amiano, Ferrán Ballester, Henrique Barros, Anna Bergström, Marie‐Aline Charles, Leda Chatzi, Cécile Chevrier, George P. Chrousos, Eva Corpeleijn, Nathalie Costet, Sarah Crozier, Graham Devereux, Merete Eggesbø, Sandra Ekström, Maria Pia Fantini, Sara Farchi, Francesco Forastiere, Vagelis Georgiu, Keith M. Godfrey, Davide Gori, Veit Grote, Wojciech Hanke, Irva Hertz‐Picciotto, Barbara Heude, Daniel Hryhorczuk, Rae‐Chi Huang, Hazel Inskip, Nina Iszatt, Anne M. Karvonen, Louise C. Kenny, Berthold Koletzko, Leanne K. Küpers, Hanna Lagström, Irina Lehmann, Per Magnus, Renata Majewska, Johanna Mäkelä, Yannis Μanios, Fionnuala M. McAuliffe, Sheila McDonald, John Mehegan, Monique Mommers, Camilla S. Morgen, Trevor A. Mori, George Moschonis, Deirdre Murray, Carol Ní Chaoimh, Ellen A. Nøhr, Anne‐Marie Nybo Andersen, Emily Oken, Adriëtte J. J. M. Oostvogels, Agnieszka Pac, Eleni Papadopoulou, Juha Pekkanen, Costanza Pizzi, Kinga Polańska, Daniela Porta, Lorenzo Richiardi, Sheryl L. Rifas‐Shiman, Luca Ronfani, Ana Cristina Santos, Marie Standl, Camilla Stoltenberg, Elisabeth Thiering, Carel Thijs, Maties Torrent, Suzanne Tough, T. Trnovec, Steve Turner, Lenie van Rossem, Andrea von Berg, Martine Vrijheid, Tanja G. M. Vrijkotte, Jane West, Alet H. Wijga, John Wright, Олександр Звінчук, Thorkild I. A. Sørensen, Debbie A. Lawlor, Romy Gaillard, Vincent W. V. Jaddoe

Bibliographic record

VenueRECERCAT (Consorci de Serveis Universitaris de Catalunya) · 2019
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsOverweightBody mass indexWeight gainMedicinePregnancyObesityChildhood obesityPopulationOdds ratioCohort studyConfidence intervalObstetricsDemographyPediatricsInternal medicineEnvironmental healthBody weight
DOInot available

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

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)0.002
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 score0.010
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.301
Teacher spread0.250 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2019
Admission routes1
Has abstractyes

Explore more

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