{"id":"W1557521848","doi":"","title":"Human-centered systems analysis of aircraft separation from adverse weather","year":2004,"lang":"en","type":"dissertation","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Glenn Research Center; Massachusetts Institute of Technology; National Aeronautics and Space Administration","keywords":"Separation (statistics); Aeronautics; Environmental science; Adverse weather; Meteorology; Engineering; Computer science; Geography; Machine learning","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009696602,0.0005206002,0.001114739,0.002817812,0.00008552858,0.00002275688,0.0005669871,0.001133558,0.0001055056],"category_scores_gemma":[0.00003707499,0.0005798923,0.0003678044,0.002022995,0.0001279132,0.0002990895,0.00004124099,0.0003994859,0.00001732856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002486722,"about_ca_system_score_gemma":0.00005695403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002193574,"about_ca_topic_score_gemma":0.001814254,"domain_scores_codex":[0.9978152,0.00001696448,0.0009382367,0.0004959555,0.0004217146,0.000311909],"domain_scores_gemma":[0.9982977,0.00001139935,0.0006143142,0.000829122,0.0001975502,0.00004993697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003302164,0.0001579772,0.001718099,0.0007409238,0.007208566,0.00001612278,0.0005855099,0.9797969,0.002772389,0.003818343,0.001897633,0.001254505],"study_design_scores_gemma":[0.01220556,0.000830093,0.03296983,0.007970612,0.05259009,0.000004127907,0.009558724,0.6799719,0.0325857,0.001223483,0.1625355,0.007554364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399821,0.003579898,0.02565271,0.000166237,0.003906112,0.001894344,0.0008873909,0.002413508,0.02151765],"genre_scores_gemma":[0.988015,0.0002996721,0.002920532,0.000005161285,0.00005682892,0.00008627881,0.006167601,0.00008824652,0.002360658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.299825,"threshold_uncertainty_score":0.9996653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009812527034560106,"score_gpt":0.2462511751150864,"score_spread":0.2364386480805263,"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."}}