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Record W2942415038 · doi:10.17863/cam.41876

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

2019· article· en· W2942415038 on OpenAlexfundno aff
Christel M. Middeldorp, Janine F. Felix, Anubha Mahajan, Mark I. McCarthy

Bibliographic record

VenueUniversity of Southern Denmark Research Portal (University of Southern Denmark) · 2019
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsnot available
FundersRIKENInstituto de Salud Carlos IIIGreat Ormond Street Institute of Child HealthForsknings- og InnovationsstyrelsenDanish Agency for Science and Higher EducationManchester Biomedical Research CentreMax Planck Instituut voor PsycholinguïstiekTurun YliopistosäätiöCentro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas AsociadasDiabetestutkimussäätiöNational Institute of Diabetes and Digestive and Kidney DiseasesTurun Yliopistollinen KeskussairaalaGovernment of Western AustraliaRegion SjællandFaculty of Health and Medical Sciences, University of Western AustraliaDet Sundhedsvidenskabelige Fakultet, Københavns UniversitetUniversity of North Carolina at Chapel HillPaavo Nurmen SäätiöTampereen TuberkuloosisäätiöCanadian Institutes of Health ResearchSigrid Juséliuksen SäätiöSydäntutkimussäätiöTurun YliopistoUniversity of PennsylvaniaAugustinus FondenEmil Aaltosen SäätiöAsthma and Lung UKVetenskapsrådetDiabetesliittoMahidol UniversityLeids Universitair Medisch CentrumSigne ja Ane Gyllenbergin SäätiöDiamantina Institute, University of QueenslandPerelman School of Medicine, University of PennsylvaniaJuho Vainion SäätiöEuskal Herriko UnibertsitateaGeneralitat de CatalunyaImperial College LondonGeneralitat ValencianaBritish Heart FoundationMinisterio de Economía y CompetitividadNational Health and Medical Research CouncilOulun YliopistoEdith Cowan UniversitySuomen KulttuurirahastoGentofte HospitalUniversity of ExeterMurdoch UniversityCurtin University of TechnologyUniversiteit LeidenVrije Universiteit AmsterdamSchool of Public Health, Imperial College LondonUniversity of OxfordRaine Medical Research FoundationUniversity of BristolUniversité de LausanneUniversity College LondonAgència de Gestió d'Ajuts Universitaris i de RecercaLastentautien TutkimussäätiöNational Institute for Health and Care ResearchUniversitat Pompeu FabraHelsingin YliopistoSteno Diabetes Center CopenhagenLunds UniversitetAustralian GovernmentFaculty of Tropical Medicine, Mahidol UniversityMedical Research CouncilFundació la Marató de TV3Yrjö Jahnssonin SäätiöHjerteforeningenNovo Nordisk Foundation Center for Basic Metabolic ResearchUniversity of Notre DameRegion HovedstadenNovo NordiskEusko JaurlaritzaInnovationsfondenSundhed og Sygdom, Det Frie ForskningsrådItä-Suomen YliopistoFoundation for Cardiovascular ResearchChildren's Hospital of Philadelphia
KeywordsBiologyPopulation geneticsGeneticsMedical geneticsEvolutionary biologyDemographyPopulationSociologyGene

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)0.073
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.073
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0730.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.005
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.002

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 head0.039
GPT teacher head0.274
Teacher spread0.235 · 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 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

Citations0
Published2019
Admission routes1
Has abstractno

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