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IFPA meeting 2014 workshop report: Animal models to study pregnancy pathologies; new approaches to study human placental exposure to xenobiotics; biomarkers of pregnancy pathologies; placental genetics and epigenetics; the placenta and stillbirth and fetal growth restriction

2015· article· en· W2022317561 on OpenAlexaff
Sandrine Barbaux, J.J.H.M. Erwich, Phelipe Oliveira Favaron, Sophie Gil, Denis Gallot, Thaddeus G Golos, Antonio Gonzalez‐Bulnes, J Guibourdenche, Alexander Heazell, Thomas Jansson, Olivier Laprévôte, Rohan M. Lewis, R.K. Miller, David Monk, Boris Novakovic, Cees B.M. Oudejans, Mana M. Parast, P. Peugnet, Christiane Pfarrer, H Pinar, Claire T. Roberts, Wendy P. Robinson, Richard Saffery, Carlos Salomón, Amber L. Sexton, Alluri Staff, Melissa Suter, J. M. Wallace, Cathy Vaillancourt, Daniel Vaiman, Stephanie A. Worton, Gendie E. Lash

Bibliographic record

VenuePlacenta · 2015
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsInstitut National de la Recherche ScientifiqueArmand Frappier MuseumChild and Family Research InstituteUniversity of British Columbia
FundersNational Institutes of Health
KeywordsEpigeneticsPlacentaBiologyPregnancyXenobioticPlacenta DiseasesBioinformaticsPhysiologyObstetricsFetusMedicineGeneticsGene

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.313
Teacher spread0.155 · 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.

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

Citations9
Published2015
Admission routes1
Has abstractno

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