{"id":"W3114565053","doi":"10.1016/j.autcon.2020.103521","title":"3D fuzzy ergonomic analysis for rapid workplace design and modification in construction","year":2020,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":49,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Human factors and ergonomics; Reliability (semiconductor); Fuzzy logic; Human reliability; Risk analysis (engineering); Engineering; Risk assessment; Reliability engineering; Key (lock); Human error; Computer science; Poison control; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001236151,0.0001303913,0.0003047041,0.0006496503,0.0003493386,0.00001846039,0.00007463002,0.0002374071,0.0001364872],"category_scores_gemma":[0.0005475299,0.0001444962,0.00004570552,0.001372207,0.00009855743,0.0003656899,0.00002409147,0.0003526797,0.00003960056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000351155,"about_ca_system_score_gemma":0.000407123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001503706,"about_ca_topic_score_gemma":0.0001138121,"domain_scores_codex":[0.9974876,0.0007277915,0.0008618784,0.0003940554,0.0001891875,0.0003394537],"domain_scores_gemma":[0.9978801,0.001325836,0.0003196303,0.0001472115,0.0001858392,0.0001413896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001426329,0.00002938375,0.7672213,0.0004686606,0.00006402313,5.645691e-7,0.002028021,0.02211189,0.0002906671,0.01334077,0.0001990629,0.1928194],"study_design_scores_gemma":[0.001737865,0.00007146876,0.4989731,0.0000522852,0.00003539453,0.00000190021,0.001157711,0.4954856,0.00003210271,0.00195437,0.0003683715,0.0001298234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6097117,0.0001087333,0.3806424,0.004968052,0.0004631937,0.003234568,0.00003587528,0.0001384707,0.0006969796],"genre_scores_gemma":[0.9217281,0.0001660367,0.07677969,0.0002110311,0.0001458758,0.0007867251,0.0001506317,0.00001367944,0.00001826106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4733737,"threshold_uncertainty_score":0.5892384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1157300543799529,"score_gpt":0.4242366163369597,"score_spread":0.3085065619570068,"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."}}