{"id":"W1618555190","doi":"","title":"ANALYSIS OF ASAR IMAGERY FOR HYDROLOGICAL APPLICATIONS IN SARDINIA, ITALY","year":2005,"lang":"en","type":"article","venue":"","topic":"Soil Moisture and Remote Sensing","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec","funders":"","keywords":"Remote sensing; Terrain; Environmental science; Irrigation; Geology; Hydrology (agriculture); Geography; Cartography","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":[0.0005905989,0.0006612372,0.0004135756,0.001680109,0.0002489641,0.0005385713,0.0002765297,0.0002850409,0.001392665],"category_scores_gemma":[0.001021811,0.0002038856,0.0004656556,0.001835857,0.000188165,0.0002649351,0.0003208077,0.0002105586,0.0005940526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000632531,"about_ca_system_score_gemma":0.0005089457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02145961,"about_ca_topic_score_gemma":0.02757566,"domain_scores_codex":[0.9995769,0.0001041392,0.00002033668,0.00009013042,0.0001252568,0.00008328765],"domain_scores_gemma":[0.9995409,0.0001101617,0.00008910037,0.00008844907,0.0001392278,0.0000322158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001456395,0.0007411275,0.3131217,0.0007827003,0.0007339187,0.002320532,0.001001194,0.1742306,0.1005287,0.001068108,0.05087865,0.3531365],"study_design_scores_gemma":[0.00008633494,0.0001285242,0.8981218,0.00002047516,0.0001046278,0.0002795335,0.0002365556,0.08379956,0.007366307,0.0002159874,0.009602414,0.0000379891],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9758384,0.000553227,0.007056061,0.0004256343,0.00003004654,0.00013004,0.009248796,0.001433964,0.005283876],"genre_scores_gemma":[0.9484292,0.0003496075,0.02231441,0.0001137376,0.00005209964,0.0001180231,0.02655672,0.0001755519,0.001890611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02145961,"threshold_uncertainty_score":0.04266942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102427002403474,"score_gpt":0.2511366166121695,"score_spread":0.2408939163718221,"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."}}