{"id":"W4389313629","doi":"10.1109/icares60489.2023.10329794","title":"Assessment of the Potential Use of Sentinel-1 C-Band SAR Sigma-Naught and Gamma-Naught Features to Support Rice Monitoring Activities","year":2023,"lang":"en","type":"article","venue":"","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"","keywords":"Remote sensing; Sigma; Support vector machine; Computer science; Artificial intelligence; Physics; Geology","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":[0.001510196,0.0004413185,0.0003059845,0.0007336921,0.0001755182,0.0006711198,0.0003255596,0.0003183705,0.0002330934],"category_scores_gemma":[0.001747677,0.0001646619,0.0003358942,0.000589058,0.0001782453,0.0006987929,0.0003224583,0.0001869335,0.0001748413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002123181,"about_ca_system_score_gemma":0.0002632539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640349,"about_ca_topic_score_gemma":0.007284238,"domain_scores_codex":[0.9995767,0.0001456418,0.00002753492,0.00007788253,0.0001230077,0.00004927918],"domain_scores_gemma":[0.999069,0.0003405075,0.0001621683,0.00008036736,0.0003014425,0.00004645645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005439766,0.0001951567,0.7523781,0.0002072162,0.0002393594,0.0003177456,0.0002116838,0.03160743,0.05143054,0.0003663368,0.0008503631,0.1616521],"study_design_scores_gemma":[0.00002656853,0.0006186296,0.7257724,0.00007614301,0.0003081302,0.000384847,0.0005827971,0.2409886,0.0280709,0.0004122471,0.002698448,0.00006031812],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907196,0.0002851576,0.006792861,0.00009954148,0.00001499602,0.00001818088,0.0004701095,0.000117,0.001482499],"genre_scores_gemma":[0.9904327,0.0001188067,0.008813555,0.00002690682,0.00000850387,0.000009466085,0.0003435871,0.00001012754,0.0002363503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002640349,"threshold_uncertainty_score":0.007986784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01307752381657007,"score_gpt":0.2599269942632841,"score_spread":0.2468494704467141,"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."}}