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Record W1983808241 · doi:10.1002/ajmg.a.35288

Summarizing craniofacial genetics and developmental biology (SCGDB)

2014· review· en· W1983808241 on OpenAlexafffundabout
Brian K. Hall

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCraniofacialBiologyPopulationEvolutionary biologyGeneticsCraniofacial abnormalityDevelopmental biologyMedicine

Abstract

fetched live from OpenAlex

This overview article highlights active areas of research in craniofacial genetics and developmental biology as reflected in presentations given at the 34th annual meeting of the Society of Craniofacial Genetics and Developmental Biology (SCGDB) in Montreal, Quebec on October 11, 2011. This 1-day meeting provided a stimulating occasion that demonstrated the present status of research in craniofacial genetics and developmental biology and where the field is heading. To accompany the abstracts published in this issue I have selected several themes that emerged from the meeting. After discussing the basis on which craniofacial defects/syndromes are classified and investigated, I address the multi-gene basis of craniofacial syndromes with an examination of the roles of Sox9 and FGF receptors in normal and abnormal craniofacial development. I then turn to the knowledge being gained from population-wide and longitudinal cohort studies and from the discovery of new signaling centers that regulate craniofacial development.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.019

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 head0.023
GPT teacher head0.342
Teacher spread0.319 · 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
GenreReview

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

Citations6
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueAmerican Journal of Medical Genetics Part ASame topicCraniofacial Disorders and TreatmentsFrench-language works237,207