{"id":"W3022317504","doi":"","title":"Bioinformatics and Visual Genomics: Seeing Genes, Proteins and Metabolism","year":2004,"lang":"en","type":"article","venue":"Drug Metabolism Reviews","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Genomics; Computational biology; Gene; Biology; Structural genomics; Genetics; Drug metabolism; Bioinformatics; Genome; Metabolism; Biochemistry; Protein structure","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00282975,0.001999753,0.001460904,0.003413217,0.0006272511,0.005064581,0.002137858,0.001880029,0.01237801],"category_scores_gemma":[0.00748752,0.0009358507,0.00101934,0.002509103,0.002188647,0.006667371,0.002321714,0.004359966,0.006096317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001626997,"about_ca_system_score_gemma":0.001241602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005811975,"about_ca_topic_score_gemma":0.008885743,"domain_scores_codex":[0.9987125,0.000524685,0.0000569022,0.0001501271,0.0004671245,0.00008860936],"domain_scores_gemma":[0.9954852,0.002996141,0.0001451326,0.00030239,0.0005372464,0.0005339162],"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":[0.0004123115,0.00007969215,0.001075869,0.002601631,0.0002411514,0.0002123738,0.0005460043,0.004972884,0.01913311,0.07060572,0.453617,0.4465023],"study_design_scores_gemma":[0.0001348343,0.00007716579,0.002158643,0.0004903779,0.0001236993,0.0007881437,0.0003877284,0.02193644,0.007296928,0.2850399,0.6814081,0.0001580675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006074404,0.1599576,0.7118125,0.04489959,0.004281902,0.0001262269,0.003421366,0.04688041,0.02254599],"genre_scores_gemma":[0.1061216,0.1179384,0.7030463,0.0219008,0.006801088,0.0004078944,0.007908964,0.009322188,0.0265528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01237801,"threshold_uncertainty_score":0.04140854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01621893848017561,"score_gpt":0.2826219525777087,"score_spread":0.2664030140975331,"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."}}