{"id":"W4252669986","doi":"10.1201/9780849359507-25","title":"Introduction to Applied Bioinformatics","year":2005,"lang":"en","type":"book-chapter","venue":"Pharmacogenomics","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Computational biology; Biology","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003582603,0.0004560736,0.0003493769,0.0002254813,0.000109238,0.00007049481,0.0005646045,0.0004878138,0.0006426794],"category_scores_gemma":[0.00004751909,0.0004590096,0.0001877825,0.00004305676,0.0001618582,0.000004420573,0.0004881371,0.0003840692,0.00246583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001089711,"about_ca_system_score_gemma":0.0002273575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001231608,"about_ca_topic_score_gemma":0.00000636499,"domain_scores_codex":[0.9978622,0.000008002934,0.0006933959,0.0004639774,0.0004491086,0.0005233283],"domain_scores_gemma":[0.9984725,0.00001070597,0.0002148173,0.0006277696,0.0001832794,0.0004909039],"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":[0.0003359183,0.00006426619,0.000001670858,0.00024389,0.000415382,0.000003143639,0.000193148,0.0002909237,0.1327395,0.002110677,0.5018943,0.3617072],"study_design_scores_gemma":[0.0004231591,0.0001696543,0.000001682347,0.00001062876,0.00006737491,0.00001585089,0.00001878842,0.0002330307,0.03713197,0.0001776679,0.9612297,0.0005204523],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001433825,0.001143267,0.007719009,0.003701577,0.002116785,0.00205703,0.0006600832,0.00009476729,0.9810737],"genre_scores_gemma":[0.003460616,0.01462527,0.03139884,0.007470415,0.0338984,0.00008177587,0.004458506,0.0003365329,0.9042696],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4593354,"threshold_uncertainty_score":0.9997861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01866167880507079,"score_gpt":0.2773268582642182,"score_spread":0.2586651794591474,"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."}}