{"id":"W2944792157","doi":"10.1016/j.rse.2019.04.031","title":"Estimating melt onset over Arctic sea ice from time series multi-sensor Sentinel-1 and RADARSAT-2 backscatter","year":2019,"lang":"en","type":"article","venue":"Remote Sensing of Environment","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Environment and Climate Change Canada","funders":"","keywords":"Backscatter (email); Remote sensing; Arctic; Geology; Synthetic aperture radar; Temporal resolution; Terrain; Sea ice; Image resolution; Arctic ice pack; Scatterometer; Climatology; Environmental science; Wind speed; Oceanography; Cartography; Computer science; Geography; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003053221,0.0004863015,0.0002613697,0.001602925,0.0003614119,0.0005818811,0.000243033,0.0002187185,0.0003859845],"category_scores_gemma":[0.0004766427,0.000177242,0.0005661673,0.0006660637,0.0001605189,0.0003973386,0.0003443474,0.0002172849,0.0001208425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007832996,"about_ca_system_score_gemma":0.0008696234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1217221,"about_ca_topic_score_gemma":0.2623188,"domain_scores_codex":[0.9998789,0.000008228257,0.000008280163,0.00003366319,0.00003814648,0.00003284511],"domain_scores_gemma":[0.999826,0.00002375581,0.00003928933,0.000008842464,0.00007740724,0.00002476705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000296483,0.00009647694,0.8620521,0.0000856536,0.0001879677,0.0002891973,0.0003284871,0.03819077,0.04120422,0.0002594648,0.0008796233,0.05612958],"study_design_scores_gemma":[0.00001534818,0.00004299259,0.9174265,0.00003086772,0.00008938176,0.00007129038,0.0002870365,0.07392537,0.006372992,0.000134979,0.001579995,0.00002312236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951212,0.0001951968,0.002705812,0.00001691024,0.00001108127,0.00001228579,0.001130865,0.00009019711,0.0007164871],"genre_scores_gemma":[0.9904532,0.0001925256,0.005517241,0.00001530685,0.00001490289,0.00001404564,0.003408048,0.00002780716,0.000356984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1217221,"threshold_uncertainty_score":0.2420272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006919615472825338,"score_gpt":0.1878266368223917,"score_spread":0.1809070213495664,"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."}}