{"id":"W4280635490","doi":"10.3390/rs14102364","title":"Air–Sea Interface Parameters and Heat Flux from Neural Network and Advanced Microwave Scanning Radiometer Observations","year":2022,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Oceanographic and Atmospheric Processes","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Ocean Frontier Institute; Russian Science Foundation; Dalhousie University; National Natural Science Foundation of China","keywords":"Buoy; Environmental science; Wind speed; Sea surface temperature; Radiometer; Dew point; Microwave radiometer; Sensible heat; Flux (metallurgy); Remote sensing; Heat flux; Latent heat; Meteorology; Microwave; Brightness temperature; Humidity; Atmospheric sciences; Climatology; Geology; Materials science; Heat transfer; Geography; Physics","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":[0.0004558635,0.0008781136,0.0003875576,0.0007970436,0.0001797738,0.0007134345,0.0006759002,0.0008434092,0.0009220084],"category_scores_gemma":[0.001461143,0.0003824415,0.0005065592,0.0009663574,0.0002624544,0.001399076,0.0004865348,0.0007313852,0.0003120524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005672354,"about_ca_system_score_gemma":0.0004708742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01673132,"about_ca_topic_score_gemma":0.01543079,"domain_scores_codex":[0.9998168,0.00002620874,0.000008772199,0.00006468403,0.00006217583,0.00002125994],"domain_scores_gemma":[0.9997649,0.00007226662,0.00004995309,0.00002820049,0.00007127805,0.00001346834],"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":[0.0001630091,0.0001434999,0.0286182,0.000110773,0.0001821916,0.0001210352,0.00004228519,0.8366667,0.01248227,0.001291009,0.001232278,0.1189467],"study_design_scores_gemma":[0.000007312995,0.000008671048,0.005897814,0.000005837338,0.00001297316,0.000006959772,0.000003783667,0.9920198,0.001186099,0.0005579182,0.0002841627,0.000008644693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5351519,0.001282045,0.4515204,0.0003298564,0.0002847342,0.00006182458,0.001464712,0.002110194,0.007794381],"genre_scores_gemma":[0.9469352,0.0003032779,0.04911717,0.00005947338,0.0001013493,0.00005355374,0.001221252,0.00008119362,0.002127479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01673132,"threshold_uncertainty_score":0.03326786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01761971044207119,"score_gpt":0.2083125156796408,"score_spread":0.1906928052375697,"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."}}