{"id":"W2095063295","doi":"10.2316/journal.210.2010.1.210-1010","title":"COMPARISON OF CHEMICAL DESCRIPTORS FOR PROTEIN–CHEMICAL INTERACTION PREDICTION","year":2010,"lang":"en","type":"article","venue":"International Journal of Computational Bioscience","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; National Science Foundation","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000941382,0.0001535945,0.0002703587,0.0004333482,0.00005255619,0.0001700227,0.001741595,0.00008471194,0.00001323732],"category_scores_gemma":[0.0011331,0.000144523,0.0002221496,0.0003758239,0.0002203628,0.001368904,0.0002006023,0.0003523141,0.000003116204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001180106,"about_ca_system_score_gemma":0.0004623894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003264381,"about_ca_topic_score_gemma":4.448344e-7,"domain_scores_codex":[0.9970413,0.00006711148,0.001023953,0.000295575,0.001394618,0.0001774353],"domain_scores_gemma":[0.9956925,0.0006663798,0.0009865351,0.0001553492,0.00237077,0.000128494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001658174,0.0005126497,0.001452762,0.0000153679,0.00006982619,0.000003584083,0.0004310355,0.04268848,0.8532386,0.07481162,0.0004415129,0.0261687],"study_design_scores_gemma":[0.0007404388,0.0001844522,0.001911565,0.00007127559,0.00001089947,0.0001954234,0.00003855661,0.4934415,0.4423279,0.06001826,0.0009078073,0.0001519974],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4648696,0.00000979113,0.5316569,0.0008502809,0.002400589,0.0001181731,0.00001798445,0.00001713817,0.00005945225],"genre_scores_gemma":[0.6594993,3.728657e-7,0.3401494,0.00006494909,0.0002602725,0.000006539057,0.000009569064,0.000005433669,0.000004091632],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.450753,"threshold_uncertainty_score":0.5893475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03603925648432237,"score_gpt":0.381402820402145,"score_spread":0.3453635639178226,"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."}}