{"id":"W1580038529","doi":"","title":"Aircraft takeoff performance monitoring in far-northern regions: An application of the global positioning system","year":2002,"lang":"en","type":"article","venue":"University Library - University of Saskatchewan (University of Saskatchewan)","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Takeoff; Global Positioning System; Precise Point Positioning; Aeronautics; Computer science; Remote sensing; Environmental science; Meteorology; Aerospace engineering; Geology; Engineering; Telecommunications; Geography; GNSS applications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0001827043,0.0002818095,0.0004960637,0.0003229191,0.0006361353,0.000025866,0.003056098,0.0002865491,0.00004974481],"category_scores_gemma":[0.00000384147,0.0003646605,0.0002673353,0.001830827,0.0005643862,0.003402784,0.001027892,0.0003670675,0.00001495589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003093722,"about_ca_system_score_gemma":0.0002468271,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01280249,"about_ca_topic_score_gemma":0.00473595,"domain_scores_codex":[0.9978694,0.000276716,0.00027065,0.0006613687,0.0005156909,0.0004062063],"domain_scores_gemma":[0.9977071,0.00009131084,0.0006185314,0.001193941,0.0001815389,0.0002075852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000605354,0.001204371,0.6749965,0.000731774,0.0002936546,0.0003169102,0.2651193,0.01895979,0.001222992,0.002603677,0.0003123382,0.03363332],"study_design_scores_gemma":[0.002500765,0.0002696929,0.09834507,0.0007676488,0.0001419821,0.00003690444,0.8433724,0.05119501,0.0006728994,0.0001831275,0.001809722,0.000704756],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9472972,0.000102209,0.04998702,0.0004991746,0.0001929702,0.0003299285,0.0001458941,0.0002709006,0.001174674],"genre_scores_gemma":[0.9787424,0.0001040188,0.0200269,0.00001352928,0.00002819543,2.454303e-8,0.00002719191,0.00001283617,0.001044934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5782531,"threshold_uncertainty_score":0.9998806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008678177589221322,"score_gpt":0.1609277613751006,"score_spread":0.1522495837858793,"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."}}