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Record W4243707756 · doi:10.1017/s0965539512000034

FETAL DYSMORPHOLOGY

2012· article· en· W4243707756 on OpenAlexaff
Jill Clayton‐Smith

Bibliographic record

VenueFetal and Maternal Medicine Review · 2012
Typearticle
Languageen
FieldMedicine
TopicAutopsy Techniques and Outcomes
Canadian institutionsHealth Sciences Centre
Fundersnot available
KeywordsMedicineAutopsyFetusAbnormalityIn uteroObstetricsPopulationPregnancyPathology

Abstract

fetched live from OpenAlex

Congenital malformations are common, occurring in around 1 in 40 pregnancies. Analysis of data from European population-based congenital anomaly registers reported a malformation rate of 29.3 per 1000 births. Eighty percent of these were in live births whereas 17% were observed in fetuses terminated after ultrasound diagnosis of fetal abnormality. The remainder were stillborn or fetal deaths in utero. Fetal autopsy is still regarded as the gold standard procedure for identification of fetal abnormalities but assessment of the fetus by a clinical geneticist or other specialist with expertise in dysmorphology may also be informative. When coupled with other investigations which are non-invasive or involve only sampling of blood or other body fluids, examination for external malformations and dysmorphic features may complement autopsy findings or provide important information as to the causation of fetal abnormalities when autopsy is not possible. This situation is now becoming more common as rates of fetal autopsy have dropped significantly in the UK in recent years.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.336
Teacher spread0.307 · 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 designNot applicable
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
Published2012
Admission routes1
Has abstractyes

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