{"id":"W2790328543","doi":"10.15173/m.v1i32.1687","title":"Yingfu Li: A Forerunner in DNA Diagnostics","year":2018,"lang":"en","type":"article","venue":"The Meducator","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Peer review; Computational biology; Medicine; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002482348,0.0001082305,0.00009279075,0.00001559015,0.0001095331,0.00001825583,0.000264756,0.0001054696,0.00004548471],"category_scores_gemma":[0.000274436,0.00007852913,0.00006516995,0.00008038867,0.0002626753,0.000001277148,0.0000965189,0.00008204439,0.00007158602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001440581,"about_ca_system_score_gemma":0.0001233077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002698015,"about_ca_topic_score_gemma":0.0001494893,"domain_scores_codex":[0.9992522,0.0000494351,0.0001343728,0.0002190926,0.00008938084,0.0002555219],"domain_scores_gemma":[0.9993548,0.00002977723,0.00003917866,0.0004532858,0.00005508417,0.00006788773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001677985,0.0007435764,0.0984677,0.0000617485,0.0002186448,0.000007103258,0.02890778,0.00001497362,0.4251348,0.001347663,0.4326551,0.01227307],"study_design_scores_gemma":[0.0008425622,0.0005026883,0.05436296,0.00003152834,0.00004417058,0.00001584326,0.004216824,0.0000799432,0.3580657,0.001759886,0.5795882,0.0004897533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947813,0.001202405,0.0000816742,0.001071371,0.0006422078,0.0001447856,0.000005651028,0.00000720014,0.002063459],"genre_scores_gemma":[0.9941737,0.0006238554,0.0003368118,0.001381373,0.001478159,0.00003050223,0.00001438783,0.00002127345,0.00193991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.146933,"threshold_uncertainty_score":0.3202325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009686561847168401,"score_gpt":0.2628940770569989,"score_spread":0.2532075152098305,"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."}}