{"id":"W2969915353","doi":"","title":"Wind LIDAR Applications for Aviation Safety","year":2019,"lang":"en","type":"article","venue":"99th American Meteorological Society Annual Meeting","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Lidar; Aviation; Aviation safety; Aeronautics; Meteorology; Environmental science; Remote sensing; Engineering; Geography; Aerospace engineering","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":[0.0002938095,0.0001865299,0.0003283199,0.00002498391,0.0001703593,0.0000188686,0.000216583,0.0001809995,0.0000761124],"category_scores_gemma":[0.00007943646,0.0001726571,0.0002195176,0.0004218107,0.0001530544,0.0001094285,0.00005055553,0.0002621268,0.0001554664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008609575,"about_ca_system_score_gemma":0.000009657756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006415971,"about_ca_topic_score_gemma":0.000002051903,"domain_scores_codex":[0.9987909,0.0000227071,0.0002999814,0.0003160136,0.0001463621,0.0004240015],"domain_scores_gemma":[0.9992163,0.000306143,0.0001280491,0.0001831369,0.0000868804,0.00007955846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003349514,0.0005526681,0.1344155,0.0007740602,0.001258457,0.000002498179,0.006291454,0.09942466,0.1457961,0.06959833,0.0198605,0.5216908],"study_design_scores_gemma":[0.00377005,0.002659269,0.06760213,0.00007222589,0.0002800266,0.00001314818,0.02406194,0.07142854,0.01576332,0.01184867,0.7995764,0.002924276],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.74338,0.0002806721,0.2474606,0.001257736,0.0001626112,0.001553879,0.0001831289,0.001797234,0.003924231],"genre_scores_gemma":[0.9676999,0.00009928121,0.03091333,0.0007157931,0.0001628716,0.000164777,0.00005055792,0.0000323524,0.0001610712],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7797159,"threshold_uncertainty_score":0.7040755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005144135752975879,"score_gpt":0.2207454178970811,"score_spread":0.2156012821441053,"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."}}