{"id":"W4402965317","doi":"10.1029/2024jd041429","title":"Investigation of Coastal Winds and Turbulence Characteristics Using Doppler Lidar","year":2024,"lang":"en","type":"article","venue":"Journal of Geophysical Research Atmospheres","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministero dell'Università e della Ricerca; Environment and Climate Change Canada; European Commission","keywords":"Lidar; Turbulence; Doppler effect; Remote sensing; Meteorology; Environmental science; Geology; Geography; Physics; Astronomy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001785939,0.0002282092,0.0001439415,0.0007970539,0.000163985,0.0002571974,0.0001456941,0.0001782565,0.0004134237],"category_scores_gemma":[0.0002541355,0.00009289348,0.0001542542,0.0006992462,0.00008435541,0.0002090706,0.0001623539,0.0001244963,0.0001120801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446237,"about_ca_system_score_gemma":0.0001370537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005521708,"about_ca_topic_score_gemma":0.007541486,"domain_scores_codex":[0.9999331,0.00001200212,0.000005467777,0.00001564861,0.00001731319,0.00001643815],"domain_scores_gemma":[0.9998165,0.00004394514,0.00004472299,0.00001357909,0.00005170098,0.00002955057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002494107,0.0002308457,0.8988179,0.0000361152,0.00004655407,0.0005936671,0.0002313522,0.01479521,0.06234977,0.0001315191,0.0003901359,0.02212764],"study_design_scores_gemma":[0.00001600566,0.0002452603,0.9297481,0.0000101635,0.00001597559,0.000125594,0.000318944,0.06291002,0.00612424,0.00005581508,0.000412412,0.00001744065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998885,0.00001406607,0.0004950369,0.000006210251,0.000002277436,0.000004547275,0.0002355797,0.00001435281,0.0003428888],"genre_scores_gemma":[0.9990595,0.00001384326,0.000564612,0.000002372174,0.000002158106,0.000003348739,0.0002553724,0.000001676545,0.00009719315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005521708,"threshold_uncertainty_score":0.01097918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07666292321105914,"score_gpt":0.3163605941756082,"score_spread":0.2396976709645491,"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."}}