{"id":"W4243132958","doi":"10.1088/1757-899x/646/1/011001","title":"Preface","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prosperity; Beijing; Engineering ethics; Computer science; Engineering; China; Library science; Engineering management; Artificial intelligence; Political science","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":[0.0004011949,0.0001375827,0.0001823893,0.0001255188,0.00007142514,0.0003260783,0.0001361255,0.00006635303,0.000170961],"category_scores_gemma":[0.00003854389,0.0001258906,0.00001140963,0.0002718097,0.00005716727,0.0007598115,0.00004784575,0.00007043405,0.0001040096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263447,"about_ca_system_score_gemma":0.00003826348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001630094,"about_ca_topic_score_gemma":0.000001013522,"domain_scores_codex":[0.9990992,0.000005345365,0.0001793562,0.0001949851,0.000229902,0.0002912064],"domain_scores_gemma":[0.9996244,0.00001032602,0.00001927608,0.0001741131,0.00008794897,0.00008388287],"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":[0.000004386849,9.027014e-7,0.00001324552,0.00006150331,0.000002670326,7.659497e-7,0.00011924,0.002080743,0.9955268,0.001248613,0.00002412352,0.0009170115],"study_design_scores_gemma":[0.0001481778,0.00006470217,0.001380475,0.00008060035,0.000002921789,0.0000330332,0.0001563851,0.005218354,0.9850689,0.00002673199,0.007578893,0.0002408268],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941192,0.00003550401,0.0003220825,0.00001549825,0.00235389,0.0001683642,0.000005538669,0.0003105809,0.002669331],"genre_scores_gemma":[0.9995045,0.00003281643,0.0001648454,0.000006580809,0.00009457995,0.00001227586,8.475513e-7,0.00001485434,0.0001687173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01045789,"threshold_uncertainty_score":0.5133669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307770144303037,"score_gpt":0.1994718937064846,"score_spread":0.1863941922634542,"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."}}