{"id":"W2041520574","doi":"10.1159/000022955","title":"Ascertainment and Anticipation in Family Studies","year":2000,"lang":"en","type":"article","venue":"Human Heredity","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Cancer Institute","keywords":"Anticipation (artificial intelligence); Genetics; Biology; Family studies; Evolutionary biology; Psychology; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001058325,0.00005678084,0.0001285598,0.00002567314,0.00004528489,0.000005796869,0.00001739659,0.00003197787,0.00009778111],"category_scores_gemma":[0.0000818275,0.00004849755,0.00001302871,0.00004169832,0.0000484812,0.00003214825,0.00001488013,0.00007650273,0.00001772171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003294683,"about_ca_system_score_gemma":0.000007325289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002224876,"about_ca_topic_score_gemma":0.0001019873,"domain_scores_codex":[0.9995532,0.0000191727,0.0001093564,0.0001129459,0.0001023622,0.0001029453],"domain_scores_gemma":[0.9997796,0.00005465609,0.00001334772,0.00008887731,0.00001626318,0.00004727381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001837028,0.0004409211,0.8779547,0.0001996319,0.00007255785,0.0002419444,0.002425167,0.00004315921,0.0009421125,0.0005517285,0.01222862,0.1047158],"study_design_scores_gemma":[0.0008120521,0.0001716419,0.9966376,0.0001249182,0.00002139513,0.000004712678,0.0002098537,0.000104209,0.0001376762,0.0004104665,0.001309997,0.00005541847],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927849,0.00101033,0.000003037359,0.0001512128,0.00003356202,0.0001067619,0.000002566319,0.00002920964,0.005878374],"genre_scores_gemma":[0.9988841,0.0002785468,0.0001120721,0.0002014883,0.0001147251,0.000007855691,0.00001129861,0.000004278011,0.0003855807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.118683,"threshold_uncertainty_score":0.1977673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08826232376475761,"score_gpt":0.3731676979251463,"score_spread":0.2849053741603887,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}