{"id":"W2329494047","doi":"10.1177/154193120304700125","title":"Ecological Interface Design in Aviation Domains: Work Domain Analysis of Automated Collision Detection and Avoidance","year":2003,"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":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Collision avoidance; Abstraction; Domain (mathematical analysis); Collision; Aviation; Automation; Interface (matter); Computer science; Work (physics); Human–computer interaction; Systems engineering; Simulation; Engineering; Computer security; Aerospace engineering; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.001045465,0.0001518378,0.0003375557,0.0001279537,0.0002615752,0.00003877976,0.000111398,0.0001770018,0.00003875793],"category_scores_gemma":[0.000162987,0.0001203975,0.0001523905,0.0005269253,0.0001384707,0.0001849294,0.00005533813,0.0002051085,5.438613e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001149097,"about_ca_system_score_gemma":0.000008158255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005464165,"about_ca_topic_score_gemma":0.00002602709,"domain_scores_codex":[0.9988236,0.00008351041,0.0005462384,0.0002734584,0.00009918241,0.0001740008],"domain_scores_gemma":[0.998952,0.0002396561,0.0005715424,0.00006962966,0.0001265496,0.00004062956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005330054,0.0005527066,0.7333658,0.0001663258,0.001332213,2.006147e-7,0.1717139,0.00444306,0.07308006,0.01344062,0.0009517761,0.0004203664],"study_design_scores_gemma":[0.000671744,0.0001158719,0.9526812,0.00009067067,0.0001457637,0.000001411105,0.03147117,0.003870195,0.01003026,0.0006138136,0.0001175283,0.0001904013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986247,0.00005627373,0.0003830212,0.0000234357,0.000132522,0.0002292222,0.000008463686,0.0000535267,0.0004888313],"genre_scores_gemma":[0.9988913,0.00002250388,0.0009657391,0.00002497675,0.00001053514,0.0000134019,0.000001413257,0.00001016705,0.00005998673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2193154,"threshold_uncertainty_score":0.4909666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001766398671385,"score_gpt":0.2934671109496372,"score_spread":0.2734494469629234,"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."}}