{"id":"W4206420443","doi":"10.1109/lgrs.2021.3139103","title":"Superpixel-Based Cropland Classification of SAR Image With Statistical Texture and Polarization Features","year":2021,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Natural Science Foundation of China","keywords":"Random forest; Artificial intelligence; Pattern recognition (psychology); Cluster analysis; Computer science; Synthetic aperture radar; Pixel; Feature extraction; Preprocessor; Remote sensing; Mathematics; Geography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002847975,0.0004727276,0.0005899444,0.001585977,0.0001825218,0.0004449863,0.0003711132,0.0003681387,0.001123595],"category_scores_gemma":[0.0003684159,0.0002012232,0.0006002508,0.001223554,0.0001964597,0.0008219551,0.0002437517,0.000249018,0.0006485963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000203894,"about_ca_system_score_gemma":0.0002377384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002289882,"about_ca_topic_score_gemma":0.004755252,"domain_scores_codex":[0.9997907,0.00002415465,0.00001024305,0.00006763211,0.00007336308,0.00003382349],"domain_scores_gemma":[0.9998078,0.00002918284,0.00003071797,0.0000323592,0.00008350208,0.00001636424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003097875,0.0001141175,0.01142774,0.0002378934,0.0001492225,0.0002197786,0.00008939542,0.03885403,0.2071265,0.001390818,0.003522439,0.7365583],"study_design_scores_gemma":[0.00002099654,0.0001004511,0.03326604,0.00002272576,0.0001030323,0.0004272303,0.0001021276,0.9114744,0.04865954,0.001811239,0.003971202,0.00004098779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1810875,0.0009707108,0.8117159,0.0001016883,0.00008788097,0.00007592456,0.0005126719,0.001666453,0.003781231],"genre_scores_gemma":[0.5504976,0.0006749981,0.4444556,0.0001001663,0.00007698336,0.00006442526,0.001576545,0.0001491964,0.002404529],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002289882,"threshold_uncertainty_score":0.004553139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005405538180538311,"score_gpt":0.2075921953930783,"score_spread":0.2021866572125399,"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."}}