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Record W2768220050 · doi:10.1016/j.vaccine.2017.01.044

Congenital microcephaly: Case definition & guidelines for data collection, analysis, and presentation of safety data after maternal immunisation

2017· article· en· W2768220050 on OpenAlexaff
Malini B. DeSilva, Flor M. Muñoz, Erick Sell, Helen Marshall, Alison Tse Kawai, Alisa Kachikis, Paul T. Heath, Nicola P. Klein, James M. Oleske, Fyezah Jehan, Hans Spiegel, Mirjana Nesin, Beckie N. Tagbo, Anju Shrestha, Clare Cutland, Linda O. Eckert, Sonali Kochhar, Azucena Bardají

Bibliographic record

VenueVaccine · 2017
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsChildren's Hospital of Eastern Ontario
FundersBill and Melinda Gates Foundation
KeywordsMicrocephalyMedicinePediatricsPresentation (obstetrics)Data collectionData presentationIntensive care medicineObstetrics

Abstract

fetched live from OpenAlex

Need for developing case definitions and guidelines for data collection, analysis, and presentation for congenital microcephaly as an adverse event following maternal immunisation Congenital microcephaly, also referred to as primary microcephaly due to its presence in utero or at birth, is a descriptive term

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)0.109
metaresearch head score (Gemma)0.184
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: Methods · Consensus signal: Methods
Teacher disagreement score0.109
Threshold uncertainty score0.577

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1090.184
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0110.007
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0050.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0090.013

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 head0.166
GPT teacher head0.413
Teacher spread0.248 · 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
GenreMethods

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

Citations67
Published2017
Admission routes1
Has abstractyes

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