{"id":"W2006827865","doi":"10.1093/humrep/deh505","title":"Regulatory approaches to reproductive genetic testing","year":2004,"lang":"en","type":"article","venue":"Human Reproduction","topic":"Reproductive Health and Technologies","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Johns Hopkins University; Pew Charitable Trusts","keywords":"Legislature; Reproductive rights; Genetic testing; Legislation; Reproductive health; Confidentiality; Political science; Reproductive technology; Public health; Law; Medicine; Environmental health; Population; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006609556,0.0002247915,0.0003284552,0.0003410843,0.0003353407,0.00002212133,0.0001141084,0.0001204036,0.00001216302],"category_scores_gemma":[0.00197131,0.0002115452,0.00006902759,0.0008172311,0.0001987737,0.0001026874,0.00008860652,0.0003367467,0.0001142108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003272605,"about_ca_system_score_gemma":0.0001400578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001009854,"about_ca_topic_score_gemma":0.000005100947,"domain_scores_codex":[0.9969801,0.00003408375,0.0004196168,0.001822073,0.0003323728,0.0004117957],"domain_scores_gemma":[0.9971805,0.00001023844,0.0001480081,0.002253742,0.0002454158,0.0001620559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007557691,0.001913233,0.09922417,0.001161759,0.0002595037,0.000187289,0.003777895,0.006374289,0.435022,0.04106506,0.002625427,0.4076336],"study_design_scores_gemma":[0.0008080033,0.001189969,0.7735361,0.000136902,0.00007446662,0.0009326843,0.0004573084,0.000002767307,0.1912263,0.02646863,0.004823357,0.0003434684],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829116,0.0006663246,0.0003889606,0.008919779,0.0003921907,0.001385396,7.670908e-7,0.0009057052,0.004429291],"genre_scores_gemma":[0.9599863,0.000007535464,0.03635862,0.0001404452,0.002085052,0.0001580384,0.000008710186,0.00004776658,0.001207516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.674312,"threshold_uncertainty_score":0.8626563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2644123494539546,"score_gpt":0.3177945507373036,"score_spread":0.05338220128334897,"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."}}