{"id":"W4299956229","doi":"","title":"Ismb 2002. Proceedings of the 10th International Conference on Intelligent Systems for Molecular Biology. Edmonton, Canada, August 3-7, 2002.","year":2002,"lang":"en","type":"other","venue":"PubMed","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Library science; Computer science; Computational biology; Operations research; Biology; Engineering","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":[0.003227684,0.002545081,0.002431561,0.003857019,0.00114093,0.005496214,0.002175883,0.001680359,0.1261063],"category_scores_gemma":[0.004381006,0.001128513,0.0009683048,0.004198831,0.0007057287,0.004441602,0.002021289,0.002489092,0.1583523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766754,"about_ca_system_score_gemma":0.004446536,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02582769,"about_ca_topic_score_gemma":0.07647157,"domain_scores_codex":[0.9991539,0.0001807786,0.000102951,0.0001461022,0.0003521565,0.00006415688],"domain_scores_gemma":[0.9956943,0.00107894,0.0001579472,0.0004735362,0.001742761,0.0008524663],"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":[0.0001103811,0.00006688444,0.000240633,0.0005556676,0.00003976991,0.00008034111,0.00005401291,0.0002909889,0.001189202,0.001367094,0.8529348,0.1430702],"study_design_scores_gemma":[0.00002905801,0.00001724843,0.0009612773,0.0002723859,0.00005603403,0.0001783601,0.00007822914,0.001006954,0.0008660332,0.002085677,0.9944255,0.0000232175],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007141146,0.1573113,0.2008597,0.03063225,0.03245869,0.001328705,0.1281718,0.06475411,0.3773423],"genre_scores_gemma":[0.006657329,0.0754907,0.09335446,0.003309477,0.002215474,0.0005462457,0.1724923,0.007139255,0.6387948],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9741723,"threshold_uncertainty_score":0.4218675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02630247172605924,"score_gpt":0.2460715035950375,"score_spread":0.2197690318689783,"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."}}