{"id":"W1983257394","doi":"10.1002/cmdc.200900091","title":"Clinical Bioinformatics. Edited by Ronald J. A. Trent.","year":2009,"lang":"en","type":"article","venue":"ChemMedChem","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computational biology; Bioinformatics; Library science; Computer science; Biology","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":[0.0005910223,0.0002484814,0.0002781928,0.00005992222,0.00008678645,0.00005543552,0.0005151639,0.0004301127,0.000100484],"category_scores_gemma":[0.000494289,0.0002107066,0.0002170127,0.0001647422,0.0003027184,0.000009090368,0.0001445883,0.0002830428,0.0001940175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002238901,"about_ca_system_score_gemma":0.000124774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002699195,"about_ca_topic_score_gemma":0.000002168483,"domain_scores_codex":[0.9978445,0.00003317613,0.0007274097,0.000319017,0.0004793457,0.000596593],"domain_scores_gemma":[0.998647,0.00003283278,0.0001472748,0.0005393034,0.0001447449,0.0004888796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008013872,0.0003130689,0.0004552629,0.00004011856,0.00006113158,0.000002134794,0.0000633055,6.027088e-7,0.1035345,0.00002161272,0.7268676,0.1685605],"study_design_scores_gemma":[0.001183014,0.0007035643,0.001106687,0.00001821241,0.00001713855,0.000009328029,0.0001076251,0.0006410082,0.5033329,0.0001296705,0.492422,0.0003288862],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8568299,0.00334214,0.01263359,0.0133234,0.00204506,0.001227957,0.0002947662,0.0002342252,0.1100689],"genre_scores_gemma":[0.9649662,0.003096284,0.009255008,0.007852164,0.002262172,0.00002119185,0.002527153,0.00004225258,0.009977566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3997984,"threshold_uncertainty_score":0.8592368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02272882428396428,"score_gpt":0.3212287744171173,"score_spread":0.2984999501331531,"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."}}