{"id":"W3047099039","doi":"10.1364/oe.397126","title":"In situ evaluation of spaceborne CALIOP lidar measurements of the upper-ocean particle backscattering coefficient","year":2020,"lang":"en","type":"article","venue":"Optics Express","topic":"Atmospheric and Environmental Gas Dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Takuvik Joint International Laboratory; Université Laval","funders":"Horizon 2020 Framework Programme; National Aeronautics and Space Administration; Canada First Research Excellence Fund; Canada Excellence Research Chairs, Government of Canada; Centre National d’Etudes Spatiales; European Research Council; Government of Canada","keywords":"Argo; Lidar; Environmental science; Remote sensing; Correlation coefficient; Biogeochemical cycle; Meteorology; Climatology; Geology; Geography; Mathematics; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003477711,0.00009078588,0.0001211808,0.000002269703,0.00002974604,0.000005654264,0.0002337909,0.00003403551,0.0001685797],"category_scores_gemma":[0.0000432955,0.0000741066,0.00004246918,0.0001759192,0.0001590936,0.00006469102,0.0002673235,0.00006604117,0.00001351421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001276627,"about_ca_system_score_gemma":0.000007647363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006558758,"about_ca_topic_score_gemma":0.00001241385,"domain_scores_codex":[0.9986609,0.0000826365,0.0002361402,0.0001774332,0.0006858242,0.0001570847],"domain_scores_gemma":[0.9995853,0.00001304814,0.0001119614,0.0002209135,0.000008443527,0.00006029504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001435877,0.0001083292,0.1432611,0.00001086641,0.000005616805,3.629351e-7,0.001440503,0.6028112,0.2518641,0.00001493491,0.00001966221,0.0004490258],"study_design_scores_gemma":[0.001186633,0.00009943402,0.1941508,0.00005138635,0.00007253227,0.000001098856,0.0008927443,0.4509089,0.3522087,0.00008884943,0.0001273568,0.000211509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952798,0.00001974642,0.001300212,0.0002896835,0.00004811093,0.0002498582,0.000002003851,0.00000429548,0.002806211],"genre_scores_gemma":[0.99626,0.000004684223,0.003551982,0.0001250372,0.000008420459,0.000004618365,7.055085e-7,0.00001058457,0.00003397099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1519023,"threshold_uncertainty_score":0.3021979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03307896272580123,"score_gpt":0.2458529849298079,"score_spread":0.2127740222040067,"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."}}