{"id":"W1994204378","doi":"10.1117/1.3662866","title":"Combining land surface temperature and shortwave infrared reflectance for early detection of mountain pine beetle infestations in western Canada","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Remote Sensing","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mountain pine beetle; Environmental science; Remote sensing; Canopy; Dendroctonus; Vegetation (pathology); Stage (stratigraphy); Ecology; Geography; Forestry; Bark beetle; Geology; Biology","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":[0.0002219918,0.0003456812,0.0002566663,0.00134285,0.001260279,0.000931963,0.0004887543,0.0002287602,0.001194276],"category_scores_gemma":[0.0004696882,0.0002409765,0.00015987,0.001454144,0.0002419623,0.0001890895,0.0002389635,0.0002845302,0.0002675374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006859973,"about_ca_system_score_gemma":0.006705152,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9866654,"about_ca_topic_score_gemma":0.9969124,"domain_scores_codex":[0.9997723,0.0000140906,0.000009076861,0.00004993502,0.00009010919,0.00006462565],"domain_scores_gemma":[0.9994222,0.00002587111,0.00004402628,0.000009721744,0.0003976528,0.0001004758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003634413,0.0001484148,0.9307618,0.00007982567,0.00009942426,0.0003576607,0.0008165367,0.001011574,0.02834238,0.00006670008,0.00140391,0.03654835],"study_design_scores_gemma":[0.000006731642,0.00002544401,0.9949687,0.00001549382,0.00002203804,0.00005108707,0.0008540781,0.00187552,0.001187063,0.00001156126,0.0009682528,0.00001402405],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949539,0.0003896731,0.0004260004,0.00004994361,0.000005317045,0.00005480045,0.001292011,0.00005954197,0.002768605],"genre_scores_gemma":[0.9950386,0.000294449,0.00160898,0.0000427995,0.000001619847,0.00001563579,0.0009293827,0.00001207911,0.00205647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01333463,"threshold_uncertainty_score":0.0497728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009723382865108331,"score_gpt":0.2100217776989589,"score_spread":0.2002983948338505,"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."}}