{"id":"W2770241087","doi":"","title":"RADARSAT-2 Polarimetric Radar Imaging for Lake Ice Mapping","year":2016,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Polarimetry; Radar imaging; Early-warning radar; Geology; Radar; Geography; Computer science; Radar engineering details; Physics; Optics; Scattering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002933675,0.0002775691,0.0001731278,0.0007625595,0.0002131168,0.0003751147,0.0001863206,0.0001486103,0.001327044],"category_scores_gemma":[0.0004415096,0.0001219902,0.0001834694,0.001005723,0.0001271594,0.0002946772,0.0002664446,0.000240091,0.0005311387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004055734,"about_ca_system_score_gemma":0.0008937948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03316729,"about_ca_topic_score_gemma":0.06708871,"domain_scores_codex":[0.9998904,0.00002233155,0.000003141903,0.00001689041,0.00005054157,0.00001666048],"domain_scores_gemma":[0.9998689,0.00002642293,0.00001972884,0.00002122004,0.000055487,0.000008186799],"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":[0.0002060793,0.00011192,0.03321161,0.0003425517,0.0001046921,0.0002389489,0.0002582855,0.0426798,0.1738588,0.005921838,0.01291003,0.7301554],"study_design_scores_gemma":[0.00004910669,0.0001647822,0.1762329,0.0001280875,0.0001715581,0.0004552162,0.0003483187,0.7047216,0.05561119,0.007318488,0.05470161,0.00009713644],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.279999,0.005204551,0.6746139,0.00101069,0.0001195998,0.0004599284,0.008000746,0.002632943,0.02795863],"genre_scores_gemma":[0.6965796,0.003467503,0.2863209,0.0001794233,0.00007860969,0.0001578607,0.00617654,0.0001303714,0.006909281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03316729,"threshold_uncertainty_score":0.06594849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008045778844008937,"score_gpt":0.1808998474528537,"score_spread":0.1728540686088448,"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."}}