{"id":"W2005186760","doi":"10.3390/ijgi3010254","title":"Investigating Forest Disturbance Using Landsat Data in the Nagagamisis Central Plateau, Ontario, Canada","year":2014,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tembec; Toronto Metropolitan University","funders":"","keywords":"Geography; Disturbance (geology); National park; Plateau (mathematics); Forestry; Land cover; Physical geography; Nature reserve; Land use; Remote sensing; Cartography; Ecology; Archaeology; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000227164,0.0002023599,0.0001893314,0.001773573,0.001436478,0.001135443,0.0004273393,0.0001824896,0.001027984],"category_scores_gemma":[0.001002481,0.000159745,0.0001817381,0.004700252,0.0004119893,0.0002939224,0.0003558132,0.0001785683,0.0001851041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01315562,"about_ca_system_score_gemma":0.01484461,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958495,"about_ca_topic_score_gemma":0.9987387,"domain_scores_codex":[0.9997256,0.0000133335,0.00001406475,0.00004202273,0.0001248276,0.00008008832],"domain_scores_gemma":[0.9989976,0.00007464107,0.0001168002,0.00002802339,0.0006559744,0.0001269674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001340745,0.00005944729,0.9633426,0.0001213286,0.00007658303,0.000524865,0.002205301,0.001942888,0.003989392,0.0002324013,0.003116056,0.02425518],"study_design_scores_gemma":[0.00000387347,0.000006868224,0.9954283,0.00001489499,0.00001087888,0.00002620362,0.001326256,0.001145776,0.0001673172,0.00001291081,0.001850303,0.000006275336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880604,0.000437401,0.0003126405,0.00009568747,0.000005193943,0.00006657104,0.006521033,0.00002600486,0.004475086],"genre_scores_gemma":[0.9904816,0.0004902418,0.0008244091,0.00002576099,0.000003942198,0.00003169016,0.005207396,0.000008888551,0.002926095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01315562,"threshold_uncertainty_score":0.09545118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01225959304307135,"score_gpt":0.2293792696016953,"score_spread":0.2171196765586239,"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."}}