{"id":"W3135265717","doi":"","title":"Atmospheric temperature retrievals from lidar measurements using techniques of non-linear mathematical inversion","year":2011,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Calibration and Measurement Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lidar; Remote sensing; Environmental science; Inversion (geology); Meteorology; Atmospheric temperature; Atmospheric sciences; Geography; Geology","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0003163299,0.0003153991,0.0003970062,0.0001452769,0.00008964774,0.00005334422,0.0004841637,0.0003400554,0.0001035521],"category_scores_gemma":[0.00002459451,0.00034621,0.0001468256,0.0004996799,0.00007927944,0.00109668,0.0001376849,0.0003994874,0.00003455663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002214065,"about_ca_system_score_gemma":0.00005110409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007176562,"about_ca_topic_score_gemma":0.00004072963,"domain_scores_codex":[0.9984075,0.0001061217,0.0003661694,0.0003246737,0.0005021226,0.0002933858],"domain_scores_gemma":[0.9989739,0.00002309031,0.0001354092,0.0004889072,0.0001948166,0.0001838548],"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":[0.0001082771,0.0001413413,0.4542656,0.0001892153,0.0001512564,0.0000476664,0.0006378877,0.00002410811,0.5440001,0.0000176725,0.000004542761,0.0004122786],"study_design_scores_gemma":[0.0005179761,0.0001079435,0.07406723,0.0006168775,0.0001378663,0.000005585658,0.0001699297,0.00004479948,0.9235371,0.000129981,0.000230253,0.0004344021],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818517,0.0000552993,0.01597189,0.000005926309,0.000131593,0.0003802192,0.00002449345,0.0006753823,0.0009034878],"genre_scores_gemma":[0.9891905,0.00004475614,0.01037667,0.00006043046,0.00005260406,0.00000119031,0.00001768677,0.00006452015,0.0001915942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3801983,"threshold_uncertainty_score":0.999899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1588529704285743,"score_gpt":0.3017906068053755,"score_spread":0.1429376363768012,"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."}}