{"id":"W6907460012","doi":"10.23687/add1346b-f632-4eb9-a83d-a662b38655ad","title":"Canada Landsat Disturbance (CanLaD): a Canada-wide Landsat-based 30-m resolution product of fire and harvest detection and attribution since 1984","year":2017,"lang":"en","type":"dataset","venue":"GEOSCAN","topic":"","field":"","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Disturbance (geology); Attribution; Pixel; Change detection; Product (mathematics); Land cover; Data set","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005142004,0.0006459341,0.0008129482,0.0001398243,0.0007080232,0.000144109,0.0004318613,0.0002577019,0.00001894967],"category_scores_gemma":[0.0009787221,0.0006598032,0.00004842288,0.0002327436,0.0003335265,0.0002267017,0.0001615723,0.0005946051,0.000006890851],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00193896,"about_ca_system_score_gemma":0.006772133,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9996333,"about_ca_topic_score_gemma":0.9999762,"domain_scores_codex":[0.9964862,0.0002297617,0.0005746845,0.001083439,0.0008938423,0.0007320621],"domain_scores_gemma":[0.9966128,0.0001503964,0.001143634,0.001433537,0.0003176678,0.0003419081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002193791,0.00003230608,0.008914843,0.0006546535,0.00006129537,0.00005976485,0.000005096898,0.00002626179,0.0001440088,8.243355e-7,0.9891123,0.0007692378],"study_design_scores_gemma":[0.0008440407,0.00008708844,0.2300817,0.0003823162,0.0001888193,0.00003365475,0.000006704799,0.0002387708,0.0004360898,0.000002288414,0.7671629,0.0005357011],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05751282,0.001929467,0.00000993038,0.0006522903,0.0005903525,0.0007346679,0.9385254,0.00003602179,0.000009069809],"genre_scores_gemma":[0.262082,0.0000940235,0.00001630056,0.0001007978,0.0002524836,0.00006087114,0.737149,0.00005848226,0.0001860494],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2219495,"threshold_uncertainty_score":0.9995853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009331917926962034,"score_gpt":0.2161657246700388,"score_spread":0.2068338067430768,"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."}}