{"id":"W4283735950","doi":"10.1002/hfm.20964","title":"Applying AcciMap and STAMP to the analysis of human error in complex manual assembly","year":2022,"lang":"en","type":"article","venue":"Human Factors and Ergonomics in Manufacturing & Service Industries","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Sociotechnical system; Aerospace; Quality (philosophy); Engineering; Field (mathematics); Control (management); Process (computing); Productivity; Manufacturing engineering; Risk analysis (engineering); Process management; Computer science; Knowledge management; Business","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001321456,0.000202114,0.0005049031,0.0007672774,0.001811369,0.00003140424,0.0003579823,0.000131419,0.0004352049],"category_scores_gemma":[0.00004377916,0.0001705659,0.00003567497,0.0006991209,0.00005498201,0.0001024016,0.0007995389,0.001295298,0.000002685151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003385218,"about_ca_system_score_gemma":0.0001699963,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01699434,"about_ca_topic_score_gemma":0.06031024,"domain_scores_codex":[0.9975744,0.0004389921,0.0007692281,0.0003779283,0.0002787655,0.000560659],"domain_scores_gemma":[0.9984497,0.0007991822,0.0002262157,0.0003096613,0.00006017218,0.0001550947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000256233,0.00006023232,0.9824987,0.0002081826,0.00007475425,0.000002266018,0.01023965,0.003790525,0.0000898611,0.0007904945,0.0002962893,0.001692788],"study_design_scores_gemma":[0.0004052249,0.00007481397,0.9693969,0.00003062474,0.0000316912,2.014635e-7,0.02327312,0.0003426,0.00008093985,0.0001396887,0.0060673,0.000156891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973677,0.00003570898,0.000001325304,0.0008921897,0.00007306934,0.001152633,0.0001954824,0.00001612072,0.0002657945],"genre_scores_gemma":[0.9983986,0.00001446294,0.0000192728,0.0007030071,0.00004948215,0.0004065115,0.0002523393,0.00001902007,0.0001372966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04331591,"threshold_uncertainty_score":0.9994881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1698246177042166,"score_gpt":0.439347632714953,"score_spread":0.2695230150107364,"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."}}