{"id":"W2127852515","doi":"10.1080/10106040308542271","title":"Multi‐temporal Mapping of Burned Forest over Canada Using Satellite‐based Change Metrics","year":2003,"lang":"en","type":"article","venue":"Geocarto International","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"Canadian Forest Service; Joint Research Centre; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; European Commission","keywords":"Vegetation (pathology); Scale (ratio); Satellite; Boreal; Environmental science; Geography; Remote sensing; Taiga; Satellite imagery; Physical geography; Cartography; Meteorology; Forestry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003016356,0.000126828,0.0001440306,0.00009988873,0.00004012907,0.00001986145,0.0002154759,0.00004844841,0.0009222159],"category_scores_gemma":[0.0001773642,0.000128822,0.00004892721,0.0003699936,0.00004284421,0.0001775547,0.00005618282,0.00007370165,0.00002987928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008022453,"about_ca_system_score_gemma":0.00008889369,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5588116,"about_ca_topic_score_gemma":0.4194108,"domain_scores_codex":[0.9986197,0.00006463185,0.0002670574,0.0002294694,0.000598019,0.0002211313],"domain_scores_gemma":[0.9994627,0.00008587587,0.0001730213,0.0001683453,0.00003422252,0.00007586075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000006285399,0.0000431772,0.993798,0.0000150908,0.0000227764,0.0000216937,0.00008746842,0.00124456,0.003494031,0.00008526713,0.0001709823,0.001010703],"study_design_scores_gemma":[0.0009178576,0.00002935941,0.5658288,0.00005590694,0.00001108467,0.00001444146,0.00004605399,0.3408136,0.004022194,0.00004412192,0.08793724,0.0002793359],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917141,0.00008190732,0.004630786,0.00006480094,0.001111406,0.0002664839,0.0000476026,0.00001635101,0.002066538],"genre_scores_gemma":[0.9913922,0.000001908923,0.008125588,0.0002301528,0.00005101727,0.00001380177,0.00002904706,0.00001406433,0.000142201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4279692,"threshold_uncertainty_score":0.9999911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0386819101968596,"score_gpt":0.2468732131221538,"score_spread":0.2081913029252942,"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."}}