{"id":"W4242851878","doi":"10.1515/iupac.83.0350","title":"Compound Collection","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Field (mathematics); Computer science; Process (computing); Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Engineering; Sociology; Linguistics; Biology; Mathematics","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":[0.001666813,0.002651635,0.002292773,0.00548618,0.001201669,0.003426587,0.004158392,0.001948193,0.07990953],"category_scores_gemma":[0.007345861,0.0008034245,0.001777555,0.008065748,0.0006445079,0.002173578,0.002703625,0.003237363,0.1494883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002397223,"about_ca_system_score_gemma":0.00507572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01375669,"about_ca_topic_score_gemma":0.02597861,"domain_scores_codex":[0.9976245,0.0002952592,0.0004097177,0.0007002418,0.0007239624,0.0002464251],"domain_scores_gemma":[0.9968266,0.0005507503,0.00037303,0.0009454252,0.001017339,0.0002869055],"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":[0.0001354197,0.00004254193,0.001013119,0.0011345,0.00003460459,0.00004935157,0.0000224084,0.0003432825,0.0002873439,0.001072649,0.9893693,0.006495515],"study_design_scores_gemma":[0.000144635,0.00002039116,0.00188493,0.0002563137,0.00002454289,0.00009584943,0.00004549334,0.0002409197,0.0005542429,0.001173409,0.9955366,0.00002269002],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000160983,0.0001575553,0.0001782944,0.00004738759,0.00002862945,0.00004746982,0.9973308,0.0004211041,0.001627759],"genre_scores_gemma":[0.000254704,0.0001075893,0.0004877841,0.0000470351,0.000005395274,0.0001450004,0.9981806,0.00005534906,0.000716611],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07990953,"threshold_uncertainty_score":0.267324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02155525125641655,"score_gpt":0.4253726869970185,"score_spread":0.403817435740602,"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."}}