{"id":"W3150687497","doi":"10.3390/rs13071394","title":"Crop Monitoring and Classification Using Polarimetric RADARSAT-2 Time-Series Data Across Growing Season: A Case Study in Southwestern Ontario, Canada","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Western University","funders":"Canadian Space Agency; National Natural Science Foundation of China","keywords":"Polarimetry; Remote sensing; Synthetic aperture radar; Random forest; Observable; Radar; Environmental science; Computer science; Geography; Artificial intelligence; Physics; Scattering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002437742,0.0002006103,0.0002517475,0.00008185695,0.0002131853,0.0001141074,0.0001111585,0.00008378764,0.00000308016],"category_scores_gemma":[0.00004868459,0.0002286509,0.0000188924,0.0004859403,0.0000252683,0.0002919073,0.00016917,0.0002630873,7.366083e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005991557,"about_ca_system_score_gemma":0.0002485721,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8344332,"about_ca_topic_score_gemma":0.7965183,"domain_scores_codex":[0.9987519,0.00005428879,0.0002931062,0.000407225,0.0001957898,0.0002976232],"domain_scores_gemma":[0.9990224,0.00009089361,0.00004913298,0.0007004068,0.00005989131,0.00007729589],"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":[0.000008023236,0.00003467331,0.01852373,0.00006762294,0.00009950028,0.004823974,0.003258472,0.000128946,0.01640189,0.000002928561,0.00002064237,0.9566296],"study_design_scores_gemma":[0.001337895,0.0000489011,0.05594662,0.0007759641,0.0002951283,0.02339517,0.03281724,0.8015622,0.03262333,0.00006683588,0.04927238,0.001858261],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9525514,0.0004911323,0.04632687,0.00004355141,0.0001275323,0.0002166619,0.00001507895,0.0001348954,0.0000928598],"genre_scores_gemma":[0.7532529,0.00001083808,0.2465799,0.000008692406,0.00006647403,2.544189e-8,0.00001392114,0.00003686105,0.00003045217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9547713,"threshold_uncertainty_score":0.9324111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04260179396509276,"score_gpt":0.2843689465538263,"score_spread":0.2417671525887335,"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."}}