{"id":"W2951518131","doi":"10.1111/2041-210x.13043","title":"<scp>Remap</scp> : An online remote sensing application for land cover classification and monitoring","year":2018,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of Environment and Conservation","funders":"Australian Research Council; NSW Office of Environment and Heritage","keywords":"Computer science; Land cover; Remote sensing; Upload; Geospatial analysis; Change detection; Ancillary data; Land use; Environmental science; Data mining; Geography; Artificial intelligence; World Wide Web; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0008827363,0.00009346369,0.000120568,0.00004020804,0.000192264,0.0000136886,0.00004495154,0.0002023281,0.000001524816],"category_scores_gemma":[0.0003620794,0.00008401873,0.0000121874,0.0001436797,0.0002124313,0.0001506586,0.00004622892,0.0001120657,0.000006924513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001724302,"about_ca_system_score_gemma":0.000005680903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001598533,"about_ca_topic_score_gemma":0.0007111942,"domain_scores_codex":[0.9990059,0.0002551435,0.0001611184,0.0003348815,0.00005662374,0.0001863784],"domain_scores_gemma":[0.9994084,0.0002922666,0.000093102,0.0001359279,0.00002199165,0.00004826291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001906883,0.00003894632,0.4229596,0.00001376541,0.000005915061,4.700524e-7,0.0006128736,0.0003133424,0.2592676,0.00005257954,0.0001295699,0.3165863],"study_design_scores_gemma":[0.0001894261,0.0000795199,0.7773804,0.000007134668,0.00001119109,0.00001798444,0.0001173936,0.2142764,0.001482015,0.004689829,0.001708641,0.00004008412],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7185445,0.00002686049,0.2806287,0.0001033091,0.0001844273,0.0002211171,0.000001411682,0.00002309918,0.0002665513],"genre_scores_gemma":[0.5280316,0.00002125591,0.471647,0.00003015668,0.0001551782,6.402323e-7,0.000008897553,0.000005512798,0.00009980025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3544208,"threshold_uncertainty_score":0.3426185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03812919003126469,"score_gpt":0.3422429568589395,"score_spread":0.3041137668276748,"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."}}