{"id":"W3145346413","doi":"10.1504/ijhfe.2021.10036735","title":"Human factors of automated driving systems: a compendium of lessons learned","year":2021,"lang":"en","type":"article","venue":"International Journal of Human Factors and Ergonomics","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Compendium; Automation; Software deployment; Risk analysis (engineering); Computer science; Key (lock); Automotive industry; Process management; Systems engineering; Engineering management; Transport engineering; Engineering; Computer security; Business; Software engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002486533,0.0001674204,0.0004773545,0.0003724217,0.00009618036,0.00007640164,0.0003113743,0.0001085807,0.001403136],"category_scores_gemma":[0.00006754333,0.0001490316,0.0002263598,0.00006230213,0.00009999446,0.00021173,0.00007310747,0.0002559259,0.000005381136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001138478,"about_ca_system_score_gemma":0.00007455541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001767698,"about_ca_topic_score_gemma":0.00007678111,"domain_scores_codex":[0.9981056,0.0001439121,0.001167673,0.0001662827,0.0002764775,0.0001399895],"domain_scores_gemma":[0.9975507,0.0001738446,0.001351292,0.0001630678,0.0006618912,0.00009921238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005114021,0.002279656,0.5857643,0.0001884508,0.006197346,0.0001886279,0.03453548,0.002423923,0.1446522,0.2100226,0.01206853,0.001167476],"study_design_scores_gemma":[0.001870678,0.0002878432,0.9715724,0.0003116135,0.0000899142,0.0001506986,0.01234694,0.0005806807,0.007166365,0.0002851551,0.005066092,0.0002716252],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951903,0.00009639479,0.0001359899,0.0001164117,0.002290614,0.00004870057,0.00006766456,0.00003155072,0.002022422],"genre_scores_gemma":[0.9990244,0.00002445182,0.00004252009,0.00002038299,0.0001405,8.83868e-7,0.00004631038,0.00001914375,0.0006814041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3858081,"threshold_uncertainty_score":0.9995097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06585917239685127,"score_gpt":0.3956722257338571,"score_spread":0.3298130533370058,"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."}}