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Record W2768485829 · doi:10.1016/j.vaccine.2017.01.045

Neonatal encephalopathy: Case definition & guidelines for data collection, analysis, and presentation of maternal immunisation safety data

2017· article· en· W2768485829 on OpenAlexaff
Erick Sell, Flor M. Muñoz, Aung Soe, Max Wiznitzer, Paul T. Heath, E. Clarke, Hans Spiegel, Daphne Sawlwin, Maja Šubelj, Ilia Tikhonov, Khorshid Mohammad, Sonali Kochhar

Bibliographic record

VenueVaccine · 2017
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsFoothills Medical CentreUniversity of CalgaryChildren's Hospital of Eastern Ontario
FundersBill and Melinda Gates Foundation
KeywordsMedicinePresentation (obstetrics)EncephalopathyPediatricsIntensive care medicineMedical emergencyObstetricsInternal medicine

Abstract

fetched live from OpenAlex

To improve comparability of vaccine safety data, the acute neonatal encephalopathy working group has developed a case definition and guidelines neonatal encephalopathy applicable in study settings with different availability of resources, in healthcare settings that differ by availability of and access to health care, and in different geographic regions.

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)0.078
metaresearch head score (Gemma)0.149
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 score0.078
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0780.149
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0210.015
Science and technology studies0.0030.003
Scholarly communication0.0060.006
Open science0.0070.006
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0080.008

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 head0.152
GPT teacher head0.392
Teacher spread0.240 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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