{"id":"W1617633935","doi":"","title":"Lidar Measurements of Methane and Applications for Aircraft and Spacecraft","year":2010,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Methane; Permafrost; Atmospheric methane; Greenhouse gas; Environmental science; Atmospheric sciences; Lidar; Atmosphere (unit); Climate change; Global warming; Carbon fibers; Absorption (acoustics); Remote sensing; Meteorology; Geology; Chemistry; Materials science; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008159765,0.0004983579,0.0002468506,0.001175957,0.0003113401,0.0005523352,0.0007118542,0.0009150464,0.003970171],"category_scores_gemma":[0.0007849321,0.0002709249,0.0004244205,0.001160519,0.000141189,0.0008062365,0.0006669756,0.0004952465,0.001691076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003490331,"about_ca_system_score_gemma":0.0003658834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009345537,"about_ca_topic_score_gemma":0.00139593,"domain_scores_codex":[0.9994513,0.00008820445,0.00002411403,0.00009209781,0.0002836604,0.00006059076],"domain_scores_gemma":[0.9994992,0.00006623229,0.00004556796,0.00007934803,0.0002751202,0.00003460784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002615729,0.0001471209,0.01437244,0.0003901393,0.00006087029,0.0003757028,0.000225814,0.003106553,0.6059392,0.003483424,0.008803608,0.3628335],"study_design_scores_gemma":[0.0001456656,0.001178208,0.02710531,0.0002061997,0.0001830569,0.00167922,0.000549615,0.09649783,0.650686,0.003709459,0.2178647,0.0001947921],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3309048,0.01794064,0.5753552,0.003586577,0.002014506,0.0007441349,0.006377717,0.01079414,0.05228224],"genre_scores_gemma":[0.6044137,0.003984786,0.3738925,0.000999596,0.0003504331,0.0004116689,0.00416109,0.0002146493,0.01157148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003970171,"threshold_uncertainty_score":0.01328158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01968344721985343,"score_gpt":0.2466990179570432,"score_spread":0.2270155707371898,"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."}}