{"id":"W2025593793","doi":"10.1080/07038992.2014.987082","title":"Characterizing a Decade of Disturbance Events Using Landsat and MODIS Satellite Imagery in Western Alberta, Canada for Grizzly Bear Management","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Alberta; University of Victoria; Canadian Forest Service; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Disturbance (geology); Geography; Satellite imagery; Habitat; Ursus; Grizzly Bears; Physical geography; Land use; Environmental science; Remote sensing; Cartography; Environmental resource management; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003991166,0.0001968223,0.0001312461,0.001248704,0.0009520389,0.0006575289,0.0005257795,0.0001775095,0.000691707],"category_scores_gemma":[0.0009636745,0.0001323151,0.000132174,0.001795575,0.0003200404,0.0002618246,0.0003421796,0.0002175652,0.0001186229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009423044,"about_ca_system_score_gemma":0.007273853,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9881959,"about_ca_topic_score_gemma":0.9973108,"domain_scores_codex":[0.9998065,0.00001284053,0.000009664359,0.00003138341,0.00008368174,0.00005600185],"domain_scores_gemma":[0.9994341,0.00004141951,0.0000964506,0.00002034113,0.0002803741,0.0001273085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009233427,0.00005312607,0.9811702,0.00002216754,0.00002845152,0.0001786614,0.0007808062,0.001105172,0.001186252,0.00009149907,0.001278628,0.01401257],"study_design_scores_gemma":[0.000001797365,0.000004889235,0.9972029,0.000006442094,0.000006193588,0.00001658765,0.0008766404,0.001225291,0.0001021928,0.00001100506,0.0005423202,0.000003839493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971269,0.0001711101,0.0001729561,0.00006615087,0.000003485073,0.00001876562,0.001140399,0.00001093654,0.001289292],"genre_scores_gemma":[0.9960295,0.0002268597,0.0006519194,0.00002640277,0.000002600577,0.000009444044,0.001766336,0.000005619427,0.001281223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0118041,"threshold_uncertainty_score":0.06836933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00733445743105558,"score_gpt":0.1965016663206884,"score_spread":0.1891672088896328,"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."}}