{"id":"W1858616645","doi":"10.1007/s10897-015-9853-5","title":"Helping Couples Fulfill the “Highest of Life's Goals”: Mate Selection, Marriage Counselling, and Genetic Counseling in United States","year":2015,"lang":"en","type":"article","venue":"Journal of Genetic Counseling","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; McMaster University; Johns Hopkins University","keywords":"Genetic counseling; Selection (genetic algorithm); Public health; Human genetics; Psychology; Medicine; Family medicine; Genetics; Nursing; Biology; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002115499,0.0002405399,0.0006518255,0.0005725209,0.0001237841,0.00005065245,0.0002031166,0.0001468542,0.00001499439],"category_scores_gemma":[0.0006276371,0.0001733733,0.00007975948,0.0007767221,0.0002523163,0.00008185004,0.0000164664,0.0005561866,0.000002501606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009537875,"about_ca_system_score_gemma":0.0005045552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001722206,"about_ca_topic_score_gemma":0.00005675543,"domain_scores_codex":[0.9970578,0.0001421587,0.001429942,0.0002846591,0.0006810816,0.0004043657],"domain_scores_gemma":[0.9967119,0.0003193959,0.0009119677,0.0002937094,0.001513814,0.0002492453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004136075,0.000826294,0.6795221,0.003084901,0.001003329,0.0006496461,0.03289112,0.2034843,0.03384969,0.0002315654,0.006409285,0.03391176],"study_design_scores_gemma":[0.0299768,0.01186826,0.2965018,0.009230296,0.002350386,0.01770352,0.06890535,0.283499,0.01653217,0.05083375,0.2098174,0.002781307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9383596,0.05470595,0.004084222,0.002123291,0.0003098833,0.0003622533,0.000004440072,0.00003472564,0.00001561238],"genre_scores_gemma":[0.9110683,0.08403598,0.004183716,0.0003673859,0.0002664263,0.000006454935,0.000003831722,0.0000362035,0.00003175447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3830203,"threshold_uncertainty_score":0.7069958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249987088659854,"score_gpt":0.2772483623018432,"score_spread":0.2522496534358578,"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."}}