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Record W4213108112 · doi:10.1002/pd.5533

The 2018 Malcolm Ferguson‐Smith Young Investigator Award

2019· editorial· en· W4213108112 on OpenAlexaff
Diana W. Bianchi, Alessandro Ghidini, Brynn Levy, Jan Deprest, Tim Van Mieghem, Lyn S. Chitty, Lisa Hui, Amanda J. L. McLean‐Inglis

Bibliographic record

VenuePrenatal Diagnosis · 2019
Typeeditorial
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsMount Sinai Hospital
FundersNational Institute for Health and Care Research
KeywordsObstetrics and gynaecologyLibrary scienceMedicineFamily medicinePregnancyBiologyGenetics

Abstract

fetched live from OpenAlex

sponsorship: National Institute for Health Research (NIHR)|NIHR200250

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)0.010
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.048
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.001
Science and technology studies0.0030.003
Scholarly communication0.0100.005
Open science0.0040.003
Research integrity0.0240.025
Insufficient payload (model declined to judge)0.0370.022

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 head0.013
GPT teacher head0.266
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreEditorial

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 abstractyes

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