{"id":"W4240366064","doi":"10.1515/iupac.83.0445","title":"Radioligand","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); Multidisciplinary approach; Computer science; Process (computing); Data science; Component (thermodynamics); Management science; Sociology; Engineering; Linguistics; Biology; Mathematics; Physics; Social science","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":[0.001116655,0.002269036,0.002518067,0.00212541,0.0007456424,0.002491019,0.003742244,0.002283225,0.08435035],"category_scores_gemma":[0.005310459,0.0006418268,0.001818173,0.003453548,0.0004721313,0.001243519,0.001423442,0.002886944,0.1196055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002010514,"about_ca_system_score_gemma":0.002578234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01289815,"about_ca_topic_score_gemma":0.02409712,"domain_scores_codex":[0.9985262,0.0002302407,0.0002307516,0.000518366,0.000325938,0.0001683916],"domain_scores_gemma":[0.9980154,0.0005156318,0.0003621664,0.0005196144,0.0004120943,0.0001750312],"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":[0.0006784252,0.00008794722,0.002020294,0.002448618,0.0001020827,0.00007945089,0.00001858041,0.0004915759,0.0004926051,0.0007846784,0.9828258,0.009969919],"study_design_scores_gemma":[0.0007232322,0.0001120422,0.005681269,0.00046389,0.0001420755,0.0003981798,0.00004381146,0.0003583911,0.001374537,0.001624166,0.9890227,0.00005562817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005000384,0.0006601152,0.0002224245,0.0001497998,0.00005990968,0.00004632827,0.9953655,0.0004735527,0.002522289],"genre_scores_gemma":[0.001255699,0.0004016616,0.0005468104,0.000283509,0.00001923162,0.0002109767,0.9953223,0.00008236981,0.001877396],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08435035,"threshold_uncertainty_score":0.28218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01821812328654248,"score_gpt":0.4258887704447198,"score_spread":0.4076706471581774,"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."}}