{"id":"W4248668321","doi":"10.1515/iupac.83.0344","title":"Channel Opener","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); Computer science; Process (computing); Field (mathematics); Multidisciplinary approach; Data science; Component (thermodynamics); Sociology; Biology; Linguistics; 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":[0.001167156,0.001761016,0.001539093,0.00276933,0.001311745,0.003637587,0.002995929,0.001699898,0.07731696],"category_scores_gemma":[0.006414932,0.0005832887,0.001408249,0.004194867,0.0004543534,0.002936317,0.002372802,0.002411643,0.1561491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00113765,"about_ca_system_score_gemma":0.00251853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01025743,"about_ca_topic_score_gemma":0.02125391,"domain_scores_codex":[0.9985305,0.0001789142,0.0002044888,0.0004903945,0.0003533341,0.0002423918],"domain_scores_gemma":[0.9967846,0.0007191626,0.0003911559,0.001049549,0.0006842389,0.0003713918],"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":[0.0001646393,0.00002521956,0.001487065,0.0005418513,0.00001859759,0.00003168478,0.00002539604,0.0002008227,0.0001209255,0.0009060192,0.992593,0.003884776],"study_design_scores_gemma":[0.0002262639,0.00002951552,0.004440621,0.0003230694,0.0000321499,0.0001528597,0.00009454816,0.0005808811,0.0005092768,0.002690482,0.9908763,0.00004403797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003950214,0.0001443261,0.0001992661,0.0001119477,0.00006379401,0.00002478288,0.9952353,0.001093153,0.002732345],"genre_scores_gemma":[0.000810732,0.0001172418,0.00037948,0.0001187174,0.00001715271,0.00007411043,0.9968506,0.0001926437,0.00143948],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07731696,"threshold_uncertainty_score":0.258651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522744885928549,"score_gpt":0.4327745653725155,"score_spread":0.4075471165132301,"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."}}