{"id":"W4402136577","doi":"10.1177/10711813241277531","title":"Calibrating Trust, Reliance and Dependence in Variable-Reliability Automation","year":2024,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Innovation for Defence Excellence and Security","keywords":"Reliability (semiconductor); Task (project management); Automation; Affect (linguistics); Psychology; Computer science; Identification (biology); Reliability engineering; Social psychology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005466269,0.0004092391,0.0003401307,0.0008635363,0.0004654563,0.001479364,0.0003286845,0.0006363303,0.001014413],"category_scores_gemma":[0.04699042,0.0005305788,0.0003531227,0.0003771515,0.001050743,0.001427225,0.001213556,0.0008934048,0.0001310006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005991077,"about_ca_system_score_gemma":0.0004075647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002754629,"about_ca_topic_score_gemma":0.003069859,"domain_scores_codex":[0.99656,0.001842801,0.0002360866,0.0003182217,0.0008697498,0.0001731059],"domain_scores_gemma":[0.9420949,0.03625878,0.01157898,0.004490586,0.004138484,0.001438245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00143599,0.0008378652,0.8863918,0.0002065203,0.0003236154,0.0002574185,0.0192901,0.005625057,0.03066986,0.001770871,0.0002361593,0.05295477],"study_design_scores_gemma":[0.00003564797,0.001403654,0.9593786,0.0000672412,0.00014666,0.0003412403,0.00375298,0.02352152,0.007709444,0.002870021,0.0006546521,0.0001183807],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996678,0.00003261662,0.002585484,0.0000202104,0.000002096526,0.00001130558,0.000007179002,0.000009788297,0.0006534089],"genre_scores_gemma":[0.99918,0.00001147758,0.0007213069,0.000006214752,0.000001092879,0.000006461481,0.000007422693,0.000002605203,0.00006336193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005466269,"threshold_uncertainty_score":0.02890873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01582582121942215,"score_gpt":0.2888767764839419,"score_spread":0.2730509552645198,"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."}}