{"id":"W4309468518","doi":"10.1115/1.4056284","title":"Special Issue: Manufacturing Science Engineering Conference 2022","year":2022,"lang":"en","type":"article","venue":"Journal of Manufacturing Science and Engineering","topic":"Digital Transformation in Industry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Engineering; Library science; Government (linguistics); Manufacturing engineering; Political science; Computer science; Law","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001680096,0.0002640302,0.00028646,0.001224539,0.000477916,0.0004722486,0.001012529,0.00004288669,0.0002704847],"category_scores_gemma":[0.00009341452,0.0002784518,0.00006729572,0.0006750193,0.0002246684,0.002590369,0.0002519591,0.0009231031,0.000007182934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006141601,"about_ca_system_score_gemma":0.0001983989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002031232,"about_ca_topic_score_gemma":2.008683e-7,"domain_scores_codex":[0.9968942,0.000006174377,0.0005597976,0.0002482975,0.001603643,0.0006878786],"domain_scores_gemma":[0.9991349,0.00005968979,0.0001122607,0.0002246279,0.0001234706,0.000345045],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008232815,0.0000162721,0.00002400612,0.0001072803,0.00002274538,0.00005465529,0.0008748444,0.9542134,0.02591367,0.0003917101,0.001119374,0.01725386],"study_design_scores_gemma":[0.0007230652,0.000178261,0.005752306,0.0001705835,0.00003066993,0.001464952,0.001546551,0.05531226,0.7141929,0.00007874746,0.2196541,0.0008956019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842912,0.0001024561,0.001515454,0.0001147457,0.00526204,0.0001237862,0.000009328787,0.0001692313,0.008411756],"genre_scores_gemma":[0.9972743,0.00005506655,0.001092239,0.00002543292,0.001448795,0.000007631108,5.109053e-7,0.0000326404,0.00006336874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8989011,"threshold_uncertainty_score":0.9999667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052750606508145,"score_gpt":0.2034377948184538,"score_spread":0.1929102887533723,"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."}}