{"id":"W2426808704","doi":"10.1039/c6ra08785j","title":"Novel rhodanines with anticancer activity: design, synthesis and CoMSIA study","year":2016,"lang":"en","type":"article","venue":"RSC Advances","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Chemistry; Combinatorial chemistry; Stereochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003634736,0.0001490265,0.0002008069,0.00007152912,0.0001050052,0.00008744552,0.0003368944,0.00001622577,0.000005649187],"category_scores_gemma":[0.0001514915,0.00008696764,0.00001788985,0.0002568798,0.0001050811,0.001302611,0.0001634189,0.00004110069,0.000005322569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002964548,"about_ca_system_score_gemma":0.00006789774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001170228,"about_ca_topic_score_gemma":0.00002125145,"domain_scores_codex":[0.9987915,0.0001622948,0.0001117408,0.0004395212,0.0003023766,0.0001925434],"domain_scores_gemma":[0.9973363,0.002152304,0.00008630026,0.000294634,0.00006724164,0.00006325165],"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":[0.0001313888,0.0004276034,0.01405087,0.00002009607,0.00007670237,0.00002136897,0.0004288584,0.003232195,0.009733573,0.00763703,0.00002188493,0.9642184],"study_design_scores_gemma":[0.005499187,0.002751811,0.7358532,0.000718169,0.0001659026,0.0002816214,0.0005134963,0.09925077,0.111595,0.03476149,0.006160811,0.002448562],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1624051,0.0001843197,0.8362094,0.0007177129,0.00008582824,0.0002060873,0.000002870514,0.0000748503,0.0001138027],"genre_scores_gemma":[0.7445995,0.00003691608,0.2552021,0.00003701152,0.00003147283,0.00004114912,2.980624e-8,0.000007944796,0.00004388428],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9617699,"threshold_uncertainty_score":0.3546437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.037230636437107,"score_gpt":0.3172792900592568,"score_spread":0.2800486536221498,"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."}}