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Record W2048020253 · doi:10.1002/ajmg.1491

Soft tissue facial resemblance in families and syndrome-affected individuals

2001· article· en· W2048020253 on OpenAlexaff
Deborah J. Shaner, A. E. Peterson, Owen Beattie, J. Bamforth

Bibliographic record

VenueAmerican Journal of Medical Genetics · 2001
Typearticle
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSoft tissueMedicineGeneticsBiologyAnatomyPathology

Abstract

fetched live from OpenAlex

We investigated soft tissue facial resemblance among relatives with or without syndromes and among related and unrelated individuals diagnosed with the same syndrome. Using correlation coefficients, we compared facial landmark (i.e., three-dimensional coordinate) positions and measurements gained by photogrammetry in various combinations of normal and syndrome-affected individuals. There were fewer significant correlations for the three-dimensional coordinates and measurements between the normal parent-normal child pairs than for the normal sib pairs. There was no discernible pattern for the single measurements in the parent-child pairs, whereas all of the midline vertical measurements were significantly positively correlated in the normal sib pairs. Significant correlations were always positive in all sib comparisons, but ranged from negative to positive in all parent-child correlations. The shared environment of sibs was a possible explanation for their greater resemblance in comparison with parent-child pairs. We also had measurements from 11 subjects (related and unrelated) diagnosed with one of four syndromes, and we used these to compare individuals with the same syndrome by calculating correlation coefficients based on all available pairs of measurements. The highest significant positive correlations were found for related individuals with the same syndrome (0.72 to 0.83). Unrelated individuals with the same syndrome also had significant positive correlations, but they were lower (0.35 to 0.65). We therefore inferred that the genetic similarities between unrelated individuals with syndromes played a role in the resemblance between them, and that common genes and environment in related individuals further contributed to the high correlations found for them.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.326
Teacher spread0.300 · 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

Citations5
Published2001
Admission routes1
Has abstractyes

Explore more

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