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Overlapping clinical phenotypes: the road to identifying dysmorphology signalling pathways and their associated risks

2006· article· en· W1997100432 on OpenAlexaff
Elena Lopez‐Rangel

Bibliographic record

VenueClinical Genetics · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsSunny Hill Health Centre for ChildrenUniversity of British Columbia
Fundersnot available
KeywordsHRASCostello syndromeGeneticsKRASMedical geneticsGermline mutationPhenotypeGermlineMutationBiologyMolecular geneticsHuman geneticsGenotypeCancer researchGene

Abstract

fetched live from OpenAlex

Germline mutations in HRAS proto‐oncogene cause Costello syndrome Aoki et al. (2005) Nature Genetics 37: 1038–1040 HRAS mutations in Costello syndrome Estep et al. (2006) American Journal of Medical Genetics 10‐A: 8–16 Germline KRAS and BRAF mutations in cardio‐facio‐cutaneous syndrome Niihori et al. (2006) Nature Genetics 38: 294–296 Genotype‐phenotype correlation in Costello syndrome: HRAS mutation analysis in 43 cases Kerr et al. (2006) Journal of Medical Genetics 43: 401–405 Germline mutations in genes within the MAPK pathway cause cardio‐facio‐cutaneous syndrome Rodriguez‐Viciana et al. (2006) Science 311: 1287–1290

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.096
GPT teacher head0.363
Teacher spread0.268 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2006
Admission routes1
Has abstractyes

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