{"id":"W2129414710","doi":"10.1002/prot.20551","title":"Assessment of CAPRI predictions in rounds 3–5 shows progress in docking procedures","year":2005,"lang":"en","type":"article","venue":"Proteins Structure Function and Bioinformatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":347,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Docking (animal); Computational biology; Macromolecular docking; Computer science; Protein–ligand docking; Searching the conformational space for docking; Protein structure; Artificial intelligence; Chemistry; Virtual screening; Biology; Biochemistry; Drug discovery; Medicine","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":[0.04394697,0.003077874,0.002111561,0.003113894,0.001558007,0.004531601,0.004486077,0.001853662,0.004573712],"category_scores_gemma":[0.04725021,0.0008669226,0.00240092,0.001670731,0.001077645,0.00205901,0.004313002,0.002284699,0.003127236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002481085,"about_ca_system_score_gemma":0.003983942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007974257,"about_ca_topic_score_gemma":0.006050303,"domain_scores_codex":[0.9669139,0.0108375,0.001850127,0.004130624,0.01381517,0.002452629],"domain_scores_gemma":[0.9378918,0.02909654,0.005184509,0.008604288,0.01708189,0.002140978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.007591771,0.001474636,0.1146527,0.001619202,0.001360702,0.0009635111,0.002757833,0.2571459,0.04989508,0.004985109,0.02692927,0.5306243],"study_design_scores_gemma":[0.000393007,0.003910457,0.1217622,0.0005213359,0.0006323752,0.0006500644,0.002016057,0.7016597,0.1287927,0.003990542,0.03498891,0.0006827185],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7640753,0.00247391,0.1985038,0.001214263,0.000295705,0.001053523,0.003243949,0.01470317,0.01443636],"genre_scores_gemma":[0.8512062,0.0005758,0.1308675,0.0002987531,0.0000540182,0.0004974109,0.01083404,0.001214954,0.004451358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04394697,"threshold_uncertainty_score":0.2324166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133100212198269,"score_gpt":0.2838555535211666,"score_spread":0.272524551399184,"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."}}