{"id":"W6979860804","doi":"","title":"Análise de dados digitais multiespectrais de alta resolução obtidos pelo sensor “Compact Airborne Spectrographic Imager” em área rural do estado do Paraná - Brasil","year":2015,"lang":"en","type":"article","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thematic map; Multispectral image; Spectral bands; Reflectivity; Stereoscopy; Multispectral pattern recognition; Hyperspectral imaging","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006835248,0.0002361466,0.0002196864,0.001984704,0.0002802449,0.0005387741,0.0003155638,0.0002588143,0.0006781698],"category_scores_gemma":[0.001643581,0.0001706714,0.0002106963,0.002282906,0.0003665448,0.0003883736,0.0003492166,0.0001624397,0.0001701954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004436067,"about_ca_system_score_gemma":0.0003619862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03625559,"about_ca_topic_score_gemma":0.09184068,"domain_scores_codex":[0.9994441,0.00005799212,0.00003567302,0.0001408912,0.0002740439,0.00004738585],"domain_scores_gemma":[0.9990097,0.0003245644,0.0001815821,0.00009856123,0.0003422675,0.00004324748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002071168,0.00004706626,0.8084002,0.0003988605,0.0001478262,0.0007688275,0.006394839,0.001785341,0.05028618,0.0005625002,0.0006937972,0.1303075],"study_design_scores_gemma":[0.000002199283,0.00003239067,0.9882118,0.00003016175,0.00005507165,0.0003383355,0.002124929,0.001922562,0.003860204,0.00008825109,0.003317986,0.00001611509],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926824,0.0002163832,0.002814691,0.00003197178,0.00000477849,0.00002585001,0.0009729033,0.00008445958,0.00316658],"genre_scores_gemma":[0.9952846,0.0001535631,0.003580853,0.000006272437,0.000002956077,0.0000189445,0.0004344115,0.00001012539,0.0005083248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03625559,"threshold_uncertainty_score":0.07208914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704420391354555,"score_gpt":0.2368895958741741,"score_spread":0.2198453919606286,"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."}}