{"id":"W3005889465","doi":"","title":"Satellite data based method for general survey of forest insect disturbance in British Columbia","year":2008,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Disturbance (geology); Satellite; Remote sensing; Geography; Environmental science; Forestry; Environmental resource management; Meteorology; Geology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005726669,0.0002606965,0.0002247309,0.003152925,0.0006882524,0.0005413489,0.0004569301,0.000201957,0.003190519],"category_scores_gemma":[0.002705331,0.0002505436,0.0001922341,0.004816408,0.0001269147,0.0001895278,0.0004222431,0.0002207471,0.0006088809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00359151,"about_ca_system_score_gemma":0.004353326,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9340764,"about_ca_topic_score_gemma":0.9642217,"domain_scores_codex":[0.9995839,0.00006637575,0.00004072666,0.00009391384,0.0001483839,0.00006671509],"domain_scores_gemma":[0.9981595,0.000194028,0.0001685507,0.0001278238,0.001247838,0.000102256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002019711,0.0000838257,0.8320734,0.0001358253,0.0001128852,0.0001062956,0.0005219515,0.007831793,0.004382391,0.0003319417,0.0173983,0.1368194],"study_design_scores_gemma":[0.00002089467,0.00001393204,0.9811632,0.0000338643,0.00003686787,0.00004206148,0.0005155538,0.01139182,0.0007368835,0.00007401257,0.005954293,0.00001661543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.91487,0.0006141791,0.01104475,0.0001463676,0.00003558484,0.0005046247,0.05991975,0.0004417051,0.01242306],"genre_scores_gemma":[0.9216541,0.0004386678,0.02653277,0.0000938373,0.0000140539,0.001067968,0.03563522,0.00009022102,0.01447319],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06592357,"threshold_uncertainty_score":0.1326236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03948161549491837,"score_gpt":0.2602954812464459,"score_spread":0.2208138657515276,"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."}}