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Record W2041520574 · doi:10.1159/000022955

Ascertainment and Anticipation in Family Studies

2000· article· en· W2041520574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHuman Heredity · 2000
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsUniversité Laval
FundersNational Cancer Institute
KeywordsAnticipation (artificial intelligence)GeneticsBiologyFamily studiesEvolutionary biologyPsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Many human diseases show anticipation; that is, disease occurs earlier (or with greater severity) in successive generations. In a computer simulation, we assessed the degree of anticipation that one would expect to see in two-generation breast cancer families. Under reasonable assumed distributions for age at cancer onset, number of children, and mortality, we find a consistent earlier mean age at diagnosis in daughters than in mothers, but the same mean age at diagnosis in affected aunts and nieces. We compare these results with published pedigree data for familial breast cancer that show substantial anticipation in affected daughters compared to their mothers. We find that at least some anticipation is expected in human disease families even when the disease is stable and families are ascertained without obvious sampling bias. We further demonstrate that such anticipation is reduced when comparing affected children to the parents' affected siblings.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.088
GPT teacher head0.373
Teacher spread0.285 · 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