{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004131601,0.0003331692,0.000240118,0.0006076356,0.0003671632,0.0006951023,0.0003664021,0.0007363861,0.007121617],"category_scores_gemma":[0.0005633357,0.0002044966,0.0001915823,0.0004899459,0.0001463551,0.0008002967,0.0006229737,0.0003788558,0.001627379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000165155,"about_ca_system_score_gemma":0.0002442237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008420516,"about_ca_topic_score_gemma":0.002913006,"domain_scores_codex":[0.9998253,0.00003510322,0.000007415553,0.00002210485,0.00009015584,0.00002004922],"domain_scores_gemma":[0.999644,0.00008096552,0.00002150227,0.00003083815,0.0002021552,0.00002056682],"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":[0.000248927,0.0001121464,0.008009666,0.000424873,0.00004844195,0.0005587525,0.0002261052,0.00731479,0.2544744,0.00867148,0.02672216,0.6931881],"study_design_scores_gemma":[0.0001094381,0.001164588,0.02019074,0.0007207043,0.0002332534,0.002055705,0.001084633,0.2132664,0.2253944,0.01576267,0.5198567,0.0001608623],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.2321892,0.04226436,0.5385543,0.008545217,0.005385976,0.0002851885,0.001217175,0.004528132,0.1670303],"genre_scores_gemma":[0.8518028,0.01098138,0.09447034,0.001170004,0.0008489812,0.00007332242,0.0006667795,0.0001949467,0.03979141],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007121617,"threshold_uncertainty_score":0.02382421,"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."}}