{"id":"W2043518676","doi":"10.1177/154193120304700115","title":"Identifying Controller Strategies that Support the ‘Picture’","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":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Air traffic controller; Set (abstract data type); Computer science; Controller (irrigation); Air traffic control; Point (geometry); Representation (politics); Control (management); Risk analysis (engineering); Artificial intelligence; Engineering; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006865039,0.0002036944,0.0002490413,0.00002611302,0.0009050925,0.0002254555,0.0002949085,0.000130499,0.0003272359],"category_scores_gemma":[0.00005601115,0.0001222226,0.0002981446,0.00007790146,0.0002263881,0.0003602817,0.0000838689,0.0003479734,0.000006876934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004446314,"about_ca_system_score_gemma":0.00002070287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004189482,"about_ca_topic_score_gemma":0.00000703891,"domain_scores_codex":[0.99889,0.00002915833,0.0003906048,0.0002585311,0.0001516633,0.000280071],"domain_scores_gemma":[0.9991,0.0001279637,0.0004704212,0.0001035721,0.000144871,0.00005320202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009691746,0.0001533906,0.1513749,0.0001677041,0.0008007134,1.896666e-7,0.378755,0.00004097992,0.008552209,0.4232378,0.03659217,0.0002280255],"study_design_scores_gemma":[0.00125122,0.00007762683,0.1921645,0.00008655462,0.0001284318,0.00001683445,0.7697214,0.00006308033,0.0040954,0.006250866,0.02571811,0.000425901],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668148,0.00006825197,0.00001915514,0.0001245126,0.0005714442,0.000211839,0.0000141293,0.00005018881,0.03212565],"genre_scores_gemma":[0.9975246,0.000016758,0.00007727652,0.0002946813,0.00009167154,0.00001560006,0.000001737247,0.00002138359,0.001956273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.416987,"threshold_uncertainty_score":0.6961331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03487366974644356,"score_gpt":0.30870900457634,"score_spread":0.2738353348298964,"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."}}