{"id":"W7002157652","doi":"","title":"Materials: Canadian Genetic Non-Discrimination Act","year":2019,"lang":"en","type":"article","venue":"Waseda University Repository (Waseda University)","topic":"Fetal and Pediatric Neurological Disorders","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Legislation; Government (linguistics); Inheritance (genetic algorithm); Population; Genetic data","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006290455,0.0002541151,0.0003392033,0.0006927729,0.0003463316,0.00003076388,0.0003146698,0.0002543149,0.0007066996],"category_scores_gemma":[0.00001423113,0.0002829295,0.0001835246,0.0006370234,0.0001271235,0.0002876948,0.00009628586,0.0002558421,0.0003407742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005095672,"about_ca_system_score_gemma":0.0006011408,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02423862,"about_ca_topic_score_gemma":0.002533965,"domain_scores_codex":[0.9984286,0.0001303407,0.0001516265,0.0005548621,0.0002739437,0.0004606503],"domain_scores_gemma":[0.9986855,0.00005477629,0.00011053,0.0004334084,0.0001352998,0.0005804458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009362957,0.001965459,0.5615453,0.001743275,0.001011043,0.06295463,0.001805117,0.0005868319,0.322963,0.005932702,0.02622602,0.003903644],"study_design_scores_gemma":[0.01083774,0.00279567,0.5444151,0.00017004,0.001446107,0.0004595391,0.004691096,0.0005822895,0.01876331,0.00003785439,0.4141752,0.001626006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.86306,0.00002158442,0.00003433214,0.0003617246,0.000472487,0.0004572567,0.0000483869,0.00009757846,0.1354467],"genre_scores_gemma":[0.9598193,0.000060546,0.0001370008,0.0003071902,0.00009771545,1.147307e-7,0.00008246506,0.00001894487,0.03947676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3879492,"threshold_uncertainty_score":0.9999623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00497876366335677,"score_gpt":0.159054417534478,"score_spread":0.1540756538711212,"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."}}