{"id":"W4232102498","doi":"10.23977/etmhs.2017.1002","title":"An Analysis of Human Factors in Industrial Design Management","year":2017,"lang":"en","type":"article","venue":"Advances in Educational Technology and Psychology","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008813871,0.0000654078,0.0001417096,0.0009673118,0.0000520003,0.000006209786,0.0002033982,0.0001389796,0.00004261219],"category_scores_gemma":[0.00001365235,0.0000676491,0.00001003426,0.0002668653,0.0001217582,0.0001637677,0.00001221469,0.0001121664,2.954445e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000135221,"about_ca_system_score_gemma":0.000003723026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006533672,"about_ca_topic_score_gemma":0.00008949279,"domain_scores_codex":[0.9995582,0.00001182465,0.0001568327,0.0001484945,0.00002991175,0.00009473989],"domain_scores_gemma":[0.9996681,0.000022982,0.00005746535,0.000230152,0.000008951723,0.0000123955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001245329,0.0001162412,0.8480923,0.00001950803,0.00006882642,0.000001144497,0.0001591553,0.09142613,0.00007087454,0.04270596,0.0000110121,0.01731635],"study_design_scores_gemma":[0.0003972621,0.00005245692,0.936655,0.00001450074,0.00003645608,6.270428e-7,0.0001280537,0.001954,0.0005585706,0.05973906,0.0003530772,0.0001109208],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903207,0.0004415679,0.006759022,0.0002448986,0.000231389,0.00008970769,0.000002519318,0.00002588819,0.001884274],"genre_scores_gemma":[0.9972354,0.0005812614,0.002101774,0.000009570133,0.00001071343,0.00002753496,0.00001501074,0.000004315676,0.00001447288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08947213,"threshold_uncertainty_score":0.275865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03077094369801334,"score_gpt":0.354785509534515,"score_spread":0.3240145658365016,"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."}}