{"id":"W2163129964","doi":"10.5589/m07-001","title":"Evaluation of polarimetric L- and P-bands RAMSES data for characterizing Mediterranean vineyards","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bureau de Recherches Géologiques et Minières","keywords":"Polarimetry; Synthetic aperture radar; Land cover; Remote sensing; Cartography; Geography; C band; Cover (algebra); Mediterranean climate; Anisotropy; Land use; Biology; Physics; Scattering; Optics; Ecology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001075816,0.00008629231,0.0001788078,0.0003532835,0.00005841368,0.00003152983,0.0001156564,0.00006318161,0.000004774106],"category_scores_gemma":[0.000189243,0.00008352778,0.00003328406,0.0001744305,0.00003228599,0.0001144482,0.000006481527,0.00008951707,1.121353e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062035,"about_ca_system_score_gemma":0.0002210078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003719557,"about_ca_topic_score_gemma":0.002932452,"domain_scores_codex":[0.9992636,0.0000232545,0.0002987387,0.0000851166,0.0001894877,0.0001397659],"domain_scores_gemma":[0.9991599,0.00006586701,0.0001218242,0.0002265618,0.0003164336,0.0001094653],"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":[0.000001460525,9.952134e-7,0.00001533554,0.0000187099,0.00002409192,0.000002228703,0.00004450509,0.000003243066,0.002683879,0.00001514763,0.0009780937,0.9962123],"study_design_scores_gemma":[0.0006460628,0.00006792371,0.003194051,0.0003296538,0.0004605919,0.0006310163,0.0001429151,0.3776626,0.0316935,0.002252576,0.5826422,0.000276933],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1317415,0.003361194,0.8630211,0.0004963389,0.0002933793,0.0002240111,0.00008358469,0.00002345337,0.0007554241],"genre_scores_gemma":[0.6195369,0.0000230068,0.3801747,0.0000174139,0.0002096289,1.784967e-8,0.0000208777,0.00001570433,0.000001768652],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9959354,"threshold_uncertainty_score":0.5622882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0410632349111313,"score_gpt":0.2676663716913798,"score_spread":0.2266031367802485,"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."}}