{"id":"W2287049325","doi":"10.1002/hyp.10828","title":"Development of a rain‐on‐snow detection algorithm using passive microwave radiometry","year":2016,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Center for Northern Studies; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Snow; Environmental science; Brightness temperature; Radiometer; Precipitation; Radiometry; Climate change; Arctic; Microwave; Climatology; Meteorology; Atmospheric sciences; Remote sensing; Geology; Geography; Oceanography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001052883,0.0001133197,0.0001697257,0.00004002331,0.0002249829,0.00001118865,0.0001093397,0.00006738494,0.0004864422],"category_scores_gemma":[0.0003364823,0.00006152892,0.00003305299,0.0004624288,0.0001261387,0.00008087045,0.00001482562,0.00005113005,0.00003758229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009935275,"about_ca_system_score_gemma":0.00006396001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003693667,"about_ca_topic_score_gemma":0.0002214205,"domain_scores_codex":[0.9991394,0.00002124308,0.0002254049,0.0002241983,0.0001732283,0.0002164711],"domain_scores_gemma":[0.999311,0.0003555398,0.000114198,0.00007574769,0.0000853525,0.00005815493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004246577,0.00004158592,0.01233583,0.00002811591,0.0000350509,0.00000530326,0.0001903298,0.0002148242,0.002914816,0.0000048747,0.00003234898,0.9841545],"study_design_scores_gemma":[0.002175188,0.0014998,0.7384408,0.0003376597,0.00009189785,0.00006604272,0.001025791,0.0143713,0.1800969,0.004283134,0.05641259,0.001198918],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9200177,0.0004131875,0.07866926,0.0001558126,0.0001263618,0.0001151139,0.00002111055,0.00003747977,0.0004440184],"genre_scores_gemma":[0.9768721,0.0000845155,0.02276019,0.0001569653,0.00007193266,0.000002716693,0.000005291666,0.000002261285,0.00004405362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9829555,"threshold_uncertainty_score":0.5326201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0398235370640506,"score_gpt":0.2364415297577647,"score_spread":0.1966179926937141,"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."}}