{"id":"W3157184041","doi":"10.1016/j.isprsjprs.2021.05.013","title":"Dual-polarimetric descriptors from Sentinel-1 GRD SAR data for crop growth assessment","year":2021,"lang":"en","type":"article","venue":"ISPRS Journal of Photogrammetry and Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Synthetic aperture radar; Remote sensing; Cluster analysis; Entropy (arrow of time); Scattering; Polarimetry; Environmental science; Mathematics; Computer science; Statistics; Physics; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004716505,0.0002119294,0.0003924854,0.0002548457,0.0001464623,0.000145315,0.0001763372,0.0001483251,0.00001118997],"category_scores_gemma":[0.0002048383,0.0001879768,0.0001338022,0.0005394181,0.00005628122,0.0001611506,0.00009560191,0.0003684965,5.931236e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006200665,"about_ca_system_score_gemma":0.00006332077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002982954,"about_ca_topic_score_gemma":0.00001447912,"domain_scores_codex":[0.9986675,0.0000535026,0.0005167333,0.0002564497,0.0002401469,0.0002656444],"domain_scores_gemma":[0.9986373,0.0003255456,0.000174519,0.0004474648,0.0002643908,0.0001507987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001183248,0.00003715421,0.0001377576,0.00006284438,0.0002489391,0.00008594311,0.00004958942,0.000002589825,0.0411627,0.00003777199,0.001603135,0.9565597],"study_design_scores_gemma":[0.001134293,0.00008058673,0.001166056,0.0004369393,0.0005581957,0.00161593,0.0005024967,0.1845566,0.2478679,0.004069285,0.5574011,0.0006105934],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07321701,0.003522559,0.9219696,0.0001977682,0.0004492833,0.0001365451,0.00005005569,0.00007861722,0.0003785471],"genre_scores_gemma":[0.359486,0.0008278689,0.6392131,0.00008552722,0.000297991,1.961934e-8,0.00004102088,0.0000365701,0.00001187362],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9559491,"threshold_uncertainty_score":0.7665471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02315409510205759,"score_gpt":0.2749907635401165,"score_spread":0.251836668438059,"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."}}