{"id":"W2019652370","doi":"10.1890/130066","title":"Bringing an ecological view of change to Landsat‐based remote sensing","year":2014,"lang":"en","type":"review","venue":"Frontiers in Ecology and the Environment","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":384,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"U.S. Geological Survey; National Aeronautics and Space Administration","keywords":"Climate change; Perspective (graphical); Remote sensing; Temporal scales; Environmental change; Scale (ratio); Ecology; Natural (archaeology); Environmental resource management; Ecosystem; Global change; Computer science; Environmental science; Geography; Cartography; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009214027,0.0002662797,0.001109154,0.00006884678,0.0001094985,0.00001041977,0.0002666016,0.0002672611,0.002419637],"category_scores_gemma":[0.00003738173,0.0001813163,0.0001421915,0.0001199581,0.0005277782,0.00003452837,0.0003014332,0.0002488731,0.0001484008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005154164,"about_ca_system_score_gemma":0.000005773599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005133868,"about_ca_topic_score_gemma":0.0001285501,"domain_scores_codex":[0.9981562,0.0005006116,0.0004171006,0.0004321544,0.0001432252,0.0003507064],"domain_scores_gemma":[0.9991956,0.0001348536,0.0002136197,0.0003468856,0.000001195014,0.0001077926],"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":[0.00002395038,0.00008078352,0.00130117,0.0004222533,0.00002611563,0.00001085986,0.0001388756,0.00002603305,2.519078e-7,0.00004985469,0.0006137223,0.9973061],"study_design_scores_gemma":[0.0005615038,0.0001169538,0.009402556,0.0002851762,0.0001370186,0.000009298426,0.000096132,0.0009827344,7.433126e-7,0.0001216513,0.9880491,0.0002371702],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00495961,0.9830121,0.00395185,0.0008187951,0.001059914,0.002887267,0.00006756234,0.00003866337,0.00320422],"genre_scores_gemma":[0.002386262,0.994917,0.00165806,0.0008010765,0.00004228837,0.00003344801,0.0000595683,0.00002169231,0.0000806157],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9970689,"threshold_uncertainty_score":0.9984923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04951611076718869,"score_gpt":0.27422564589876,"score_spread":0.2247095351315713,"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."}}