{"id":"W4235433245","doi":"10.1515/iupac.83.0383","title":"High Throughput","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; Field (mathematics); Process (computing); Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Engineering; 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":[0.00222254,0.002672018,0.001852543,0.003152533,0.001378382,0.003212225,0.005422755,0.002163106,0.04929777],"category_scores_gemma":[0.00759871,0.0007143833,0.002464248,0.0055581,0.0006689889,0.002467276,0.003177271,0.002948365,0.1010446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001762272,"about_ca_system_score_gemma":0.002782896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01759815,"about_ca_topic_score_gemma":0.03474524,"domain_scores_codex":[0.9972779,0.0003982204,0.0003620942,0.0008361631,0.0007652313,0.0003603621],"domain_scores_gemma":[0.9966492,0.0005829158,0.000322624,0.0013268,0.0008104813,0.0003080097],"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":[0.0002003549,0.00005089274,0.001629381,0.0006903123,0.00005573814,0.00004477203,0.00002551778,0.0005564644,0.0002129562,0.001033691,0.9890367,0.006463204],"study_design_scores_gemma":[0.000366225,0.00005049532,0.006835357,0.0004658878,0.00006765959,0.000257446,0.00009670369,0.001394066,0.001070245,0.003639209,0.9856871,0.00006957519],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004517718,0.0002245485,0.0005099729,0.0001262809,0.00006331805,0.00004573842,0.995527,0.001121455,0.00192997],"genre_scores_gemma":[0.0005587884,0.0001006572,0.0007240286,0.00007896361,0.00001002968,0.0001070041,0.9975286,0.00009298182,0.0007989613],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04929777,"threshold_uncertainty_score":0.1649175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198964024685886,"score_gpt":0.4264246749580647,"score_spread":0.4065282724894762,"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."}}