{"id":"W65853498","doi":"","title":"Proceedings of the 5th international workshop on Bioinformatics","year":2005,"lang":"en","type":"article","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genomics; Data science; Field (mathematics); Computer science; Function (biology); Big data; Structural genomics; Translational bioinformatics; Proteomics; Knowledge extraction; DNA microarray; Class (philosophy); Bioinformatics; Genome; Computational biology; Data mining; Artificial intelligence; Biology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009122232,0.002049958,0.002468936,0.002733224,0.001603104,0.008784031,0.004430599,0.003827959,0.0732738],"category_scores_gemma":[0.01497604,0.001074244,0.002324,0.003087001,0.001429073,0.008094569,0.004553314,0.007967115,0.05238574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001512332,"about_ca_system_score_gemma":0.002810327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001538651,"about_ca_topic_score_gemma":0.001634638,"domain_scores_codex":[0.9930955,0.002596247,0.0008436979,0.001056632,0.001969165,0.0004387579],"domain_scores_gemma":[0.9889102,0.004074565,0.0002762116,0.001957958,0.003297371,0.00148364],"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":[0.0001878167,0.000146654,0.0003432643,0.0006310652,0.0001062353,0.0001999362,0.0001717614,0.001249193,0.001401987,0.01961333,0.7237025,0.2522462],"study_design_scores_gemma":[0.00003350629,0.00004941705,0.0003224481,0.0003549423,0.00002865992,0.0002592073,0.0000962347,0.004307216,0.0005366729,0.02320583,0.9707814,0.00002432633],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00551692,0.1385322,0.4491755,0.08509933,0.1081393,0.001169838,0.008234172,0.01656104,0.1875718],"genre_scores_gemma":[0.03945074,0.09174595,0.4215395,0.02814665,0.03497611,0.001844569,0.05878003,0.006182048,0.3173344],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.0732738,"threshold_uncertainty_score":0.2451253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01785462131538894,"score_gpt":0.2909676489153425,"score_spread":0.2731130275999535,"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."}}