{"id":"W2052358442","doi":"10.1109/tgrs.2012.2208649","title":"Multiyear Crop Monitoring Using Polarimetric RADARSAT-2 Data","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Defence Research and Development Canada","funders":"","keywords":"Synthetic aperture radar; Remote sensing; Backscatter (email); Environmental science; Phenology; Polarimetry; Scattering; Radar; Computer science; Agronomy; Geography; Physics; Biology","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":[0.0005106328,0.0002092904,0.0001482859,0.0008447607,0.0001781287,0.0002878787,0.0001797191,0.0001301977,0.0003706895],"category_scores_gemma":[0.0005538989,0.00007962835,0.0001145163,0.0006958118,0.00005748822,0.000412731,0.0001752944,0.0001285015,0.0001896639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003218919,"about_ca_system_score_gemma":0.0002520778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01544502,"about_ca_topic_score_gemma":0.04798231,"domain_scores_codex":[0.9997891,0.00002783532,0.00001109493,0.0000645788,0.00007565105,0.00003173686],"domain_scores_gemma":[0.9995641,0.00008109582,0.00009284974,0.00004155936,0.0001878803,0.00003250644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003839597,0.0001769333,0.7727874,0.0001279054,0.0001276568,0.0001370848,0.0002355773,0.02240113,0.08312353,0.0002040128,0.001253838,0.119041],"study_design_scores_gemma":[0.00001941957,0.0001614255,0.9157576,0.00001088663,0.00004851497,0.00009313173,0.0001228574,0.06526808,0.01575069,0.00006159231,0.002683844,0.00002203732],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866383,0.0001107384,0.009041798,0.00002060876,0.000008648157,0.00004101807,0.002331821,0.000213494,0.001593451],"genre_scores_gemma":[0.9777451,0.0001308732,0.01784004,0.0000115176,0.000007339195,0.00002760861,0.003549583,0.00002076394,0.0006672208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01544502,"threshold_uncertainty_score":0.03071022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04385941525717846,"score_gpt":0.2805462087136279,"score_spread":0.2366867934564494,"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."}}