MétaCan
Menu
Back to cohort
Record W4393347845 · doi:10.1016/j.ajcnut.2024.03.016

The Impact of Excluding Adverse Neonatal Outcomes on the Creation of Gestational Weight Gain Charts Among Women from Low- and Middle-income Countries with Normal and Overweight BMI

2024· article· en· W4393347845 on OpenAlexafffund
Thaís Rangel Bousquet Carrilho, Dongqing Wang, Jennifer A. Hutcheon, Molin Wang, Wafaie Fawzi, Gilberto Kac, Manfred Accrombessi, Seth Adu‐Afarwuah, João Guilherme Bezerra Alves, Carla Adriane Leal de Araújo, Shams El Arifeen, Rinaldo Artes, Per Ashorn, Nega Assefa, Omolola Ayoola, Fereidoun Azizi, Ahmed Tijani Bawah, Samira Behboudi‐Gandevani, Yemane Berhane, Robin M. Bernstein, Zulfiqar A Bhutta, Valérie Briand, Elvira Beatriz Calvo, Marly Augusto Cardoso, Yue Cheng, Gabriela Chico‐Barba, Peter Clayton, Shalean M. Collins, Anthony Costello, J. CRUICKSHANK, Delanjathan Devakumar, Kathryn G. Dewey, Pratibha Dwarkanath, Guadalupe Estrada‐Gutiérrez, Frankie Fair, Dayana Rodrigues Farias, Henrik Friis, Shibani Ghosh, Amy Girard, Exnevia Gomo, Austrida Gondwe, Lotta Hallamaa, K. Michael Hambidge, Hawawu Hussein, Lieven Huybregts, Romaina Iqbal, Joanne Katz, Subarna K. Khatry, Patrick Kolsteren, Nancy F. Krebs, Teija Kulmala, Pratap Kumar, Anura V. Kurpad, Carl Lachat, Anna Lartey, Jacqueline M Lauer, Qian Li, Nur Indrawaty Lipoeto, Laura Beatríz López, See Ling Loy, Arun G. Maiya, Kenneth Maleta, Maíra Barreto Malta, Dharma Manandhar, Charles Mangani, Hugo Martínez‐Rojano, Yves Martin‐Prével, Reynaldo Martorell, Susana L Matias, Elizabeth M. McClure, Alida Melse‐Boonstra, Joshua D. Miller, Marhazlina Mohamad, Hamid Jan Jan Mohamed, Sophie E. Moore, Paola Soledad Mosquera, Malay Kanti Mridha, Shama Munim, Cinthya Muñoz‐Manrique, Barnabas Natamba, Maria Ome‐Kaius, David Osrin, Otilia Perichart‐Perera, Andrew M. Prentice, Preetha Ramachandra, Usha Ramakrishnan, Dominique Roberfroid, Patricia Lima Rodrigues, Ameyalli M. Rodríguez-Cano, Stephen J. Rogerson, Patrícia Helen de Carvalho Rondó, Reyna Sámano, Naomi Saville, Siddharudha Shivalli, Bhim P Shrestha, Robin Shrestha, José Roberto da Silva, Hora Soltani, Sajid Soofi, Fahimeh Ramezani Tehrani, Tinku Thomas, James M Tielsch, Holger W. Unger, Juliana dos Santos Vaz, Alemayehu Worku, Nianhong Yang, Sera L. Young, Adam Bawa Yussif, Lingxia Zeng, Chunrong Zhong, Zhonghai Zhu

Bibliographic record

VenueAmerican Journal of Clinical Nutrition · 2024
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsUniversity of British Columbia
FundersMichael Smith Health Research BCMedical Research CouncilBill and Melinda Gates Foundation
KeywordsOverweightObstetricsMedicineWeight gainLow and middle income countriesNormal weightGestational ageNeonatal mortalityUnderweightDemographyEnvironmental healthBody weightObesityPregnancyDeveloping countryEconomicsInfant mortalityPopulationEconomic growthSociologyEndocrinology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.014
metaresearch head score (Gemma)0.126
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.126
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.002
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 head0.019
GPT teacher head0.344
Teacher spread0.325 · 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 designSimulation or modeling
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

Citations3
Published2024
Admission routes2
Has abstractno

Explore more

Same venueAmerican Journal of Clinical NutritionSame topicGestational Diabetes Research and ManagementFrench-language works237,207