{"id":"W4255896057","doi":"10.1088/1757-899x/533/1/011001","title":"Preface","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Materials Science and Engineering","topic":"Industrial Automation and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Library science; Robotics; Control (management); Political science; Engineering ethics; Artificial intelligence; Engineering management; Management; Engineering; Computer science; Law; Robot","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":[0.0003296905,0.0001356458,0.0001880269,0.00009786827,0.00005940535,0.0003426729,0.0001809524,0.00005483619,0.0002152628],"category_scores_gemma":[0.00003391093,0.0001260452,0.00001014344,0.0002128752,0.00006113893,0.0007566964,0.00003995244,0.00005822489,0.0001262784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004119549,"about_ca_system_score_gemma":0.00004948729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001253373,"about_ca_topic_score_gemma":0.000001285534,"domain_scores_codex":[0.999118,0.000005537796,0.0001869712,0.0001695266,0.0002208459,0.000299085],"domain_scores_gemma":[0.999642,0.000009421206,0.00002026361,0.0001611324,0.00008386053,0.00008337831],"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":[0.000003175818,0.000001087493,0.0000151013,0.0000623932,0.000003770647,6.526827e-7,0.0001736072,0.002614677,0.990422,0.005913197,0.00002660898,0.0007636934],"study_design_scores_gemma":[0.0003896657,0.00006283992,0.003335753,0.0001285909,0.000006108122,0.00003446039,0.0003156277,0.04252514,0.9406791,0.00005806785,0.0120183,0.0004462938],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930398,0.00003567891,0.0002132895,0.00006136631,0.001751676,0.0001915915,0.000006539679,0.0004012857,0.004298753],"genre_scores_gemma":[0.9994806,0.00002269521,0.0001339421,0.00001414885,0.00008087516,0.0000175623,0.000001426966,0.00001317118,0.0002355502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04974288,"threshold_uncertainty_score":0.5139974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01023588393524541,"score_gpt":0.1845894231854289,"score_spread":0.1743535392501835,"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."}}