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Record W2914292092 · doi:10.1002/ajmg.a.61063

39th Annual David W. Smith Workshop on Malformations and Morphogenesis: Abstracts of the 2018 Annual Meeting

2019· article· en· W2914292092 on OpenAlexafffundabout
Kym M. Boycott, A. Micheil Innes

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2019
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsAlberta Children's HospitalUniversity of CalgaryChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersNational Institute of Child Health and Human DevelopmentCumming School of Medicine, University of CalgaryMarch of Dimes Foundation
KeywordsMorphogenesisCongenital malformationsCreativityEpigeneticsEnvironmental ethicsHistoryLibrary scienceBiologyPsychologyPregnancyComputer scienceGeneticsGenePhilosophy

Abstract

fetched live from OpenAlex

The 39th Annual David W. Smith workshop on Malformations and Morphogenesis was held from August 24th-29th 2018 at the Banff Centre for Arts and Creativity, Banff, Alberta, Canada. The Workshop, which honors the legacy of David W. Smith, brought together clinicians and researchers from around the world interested in congenital malformations and their underlying mechanisms of morphogenesis in this addition to this year's five themes: phenotypes and phenotyping of known, novel and emerging syndromes; treatment; epigenetics and chromatin disorders; placenta; and, gene-environment interaction. This Conference Report includes the abstracts presented at the 2018 Workshop.

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0700.024

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 head0.027
GPT teacher head0.350
Teacher spread0.323 · 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
GenreOther

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
Published2019
Admission routes3
Has abstractyes

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