{"id":"W2786416545","doi":"","title":"Improving Polarimetric radar parameter estimates and Target Identification: a comparison of different approaches","year":2013,"lang":"en","type":"article","venue":"36th Conference on Radar Meteorology (16-20 September, 2013)","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Remote sensing; Radar; Identification (biology); Polarimetry; Computer science; Environmental science; Geology; Telecommunications; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002612281,0.0005040294,0.0008543272,0.0003600353,0.0001415319,0.00009836182,0.0004467611,0.0003802697,0.0008683314],"category_scores_gemma":[0.0001104697,0.0004312247,0.0001267475,0.0003007123,0.0003411567,0.0002107673,0.0001026247,0.0004397,0.00008839829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043305,"about_ca_system_score_gemma":0.00003429478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002519278,"about_ca_topic_score_gemma":0.00005434222,"domain_scores_codex":[0.9976722,0.0001183358,0.0008076369,0.0006033867,0.0002940081,0.0005044471],"domain_scores_gemma":[0.9979151,0.0006650489,0.0003053938,0.00079601,0.0001319576,0.0001864679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007587171,0.0009371413,0.01799531,0.0006312521,0.0006840673,0.000002570177,0.0007455014,0.00001939345,0.05776322,0.03070442,0.02409858,0.8663427],"study_design_scores_gemma":[0.002492812,0.001359103,0.03247216,0.0002048462,0.0007760854,0.000104493,0.001221916,0.2834454,0.5263564,0.06111621,0.08744531,0.003005219],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2549191,0.004803983,0.7234553,0.0007757059,0.0004253203,0.001929602,0.0000855625,0.0008370992,0.01276832],"genre_scores_gemma":[0.8314697,0.00007356442,0.1678323,0.0000522849,0.00004265485,0.0001854762,0.0000791502,0.00005903876,0.0002058917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8633375,"threshold_uncertainty_score":0.999814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02782820015091265,"score_gpt":0.2487765883245447,"score_spread":0.2209483881736321,"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."}}