{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001117376,0.000525473,0.0006907298,0.0002940983,0.0001439035,0.0002830654,0.002562979,0.0002966744,0.0007042631],"category_scores_gemma":[0.0006735089,0.000406636,0.0002369452,0.0004782043,0.0001342795,0.0005351,0.001307734,0.0004850717,0.00001284541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005506781,"about_ca_system_score_gemma":0.001766438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001355094,"about_ca_topic_score_gemma":0.0001196985,"domain_scores_codex":[0.9955634,0.000337911,0.0005896625,0.001031928,0.001940472,0.0005365577],"domain_scores_gemma":[0.9962936,0.0006258809,0.0003588347,0.001934434,0.0005942833,0.0001929767],"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":[0.00001898318,0.0001197566,4.679361e-7,0.00004699652,0.00006746464,0.00008088344,0.000009583461,0.000209787,0.000001378665,0.00329416,0.9767268,0.01942368],"study_design_scores_gemma":[0.0005644112,0.0001215717,0.00003334966,0.0001987221,0.00002895229,0.00003001631,0.000001638465,0.0004451181,0.00002187952,0.02002509,0.9780101,0.0005191668],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001229624,0.0002663041,0.2810759,0.001850139,0.00225099,0.0001748343,0.7141994,0.0001419102,0.0000281905],"genre_scores_gemma":[0.000005962693,0.000255601,0.02289678,0.0007938592,0.001244034,0.00001530195,0.9745494,0.00002948705,0.0002096239],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2603499,"threshold_uncertainty_score":0.9998385,"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."}}