{"id":"W4247513012","doi":"10.1088/1757-899x/617/1/011001","title":"Preface","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pleasure; Process (computing); Library science; Engineering ethics; Political science; Engineering; Computer science; Psychology; Neuroscience","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001903348,0.0001131318,0.0001244262,0.00009031403,0.00005933453,0.0003109139,0.0001354008,0.00003560807,0.0004077054],"category_scores_gemma":[0.00003294344,0.0001087106,0.000006613557,0.0002093697,0.00006642946,0.00118252,0.00002989183,0.00005098488,0.0001140017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002303326,"about_ca_system_score_gemma":0.0000453689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000316798,"about_ca_topic_score_gemma":0.000001338512,"domain_scores_codex":[0.9992988,0.000002494255,0.0001368421,0.0001608463,0.0001776827,0.0002232959],"domain_scores_gemma":[0.99968,0.000009132535,0.00001480046,0.0001235972,0.00009737978,0.00007502699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002423123,0.00000142286,0.00001523379,0.00009021835,0.000002104714,4.828034e-7,0.0001763809,0.003466032,0.9911079,0.004771421,0.00004575369,0.0003205669],"study_design_scores_gemma":[0.00008191341,0.00002608065,0.001611715,0.00003466402,0.000002265343,0.00002153324,0.000162616,0.007030355,0.9726104,0.0000665284,0.01814851,0.0002034433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890997,0.0000574197,0.0005095227,0.00005611089,0.0009595879,0.00009280777,0.000004183149,0.0003250682,0.008895608],"genre_scores_gemma":[0.9987096,0.0001403211,0.0004619712,0.00002092138,0.00003287848,0.00001063902,0.000001620024,0.0000110159,0.0006110254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01849759,"threshold_uncertainty_score":0.4464088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01141097821388561,"score_gpt":0.2143038489113643,"score_spread":0.2028928706974787,"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."}}