{"id":"W2066437137","doi":"10.5589/m07-036","title":"Study of landslides caused by the 1999 Chi-Chi earthquake, Taiwan, with multitemporal SPOT images","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Soil and Water Conservation Bureau; National Science Council","keywords":"Landslide; Normalized Difference Vegetation Index; Vegetation (pathology); Typhoon; Land cover; Ridge; Remote sensing; Geography; Cartography; Cohen's kappa; Physical geography; Geology; Land use; Geomorphology; Meteorology; Climate change; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008629484,0.0002209862,0.0003180614,0.0001166666,0.0002893295,0.0000790381,0.0002522697,0.00007963301,0.00002504671],"category_scores_gemma":[0.0001083185,0.0001303072,0.00008130586,0.0004535963,0.0003241646,0.000166398,0.00002479468,0.0004614287,0.000009528525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002197139,"about_ca_system_score_gemma":0.0001135428,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04282276,"about_ca_topic_score_gemma":0.3926182,"domain_scores_codex":[0.9981928,0.000122999,0.0004959197,0.0002067244,0.0005125724,0.0004689534],"domain_scores_gemma":[0.998584,0.00006650062,0.0004928867,0.0002950898,0.00008677622,0.0004747844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002585468,0.000155938,0.1277193,0.00002705082,0.0004286553,0.008448544,0.02837513,0.005380336,0.04594847,0.000002176636,0.04994483,0.733311],"study_design_scores_gemma":[0.003798657,0.001627325,0.8717939,0.0005095341,0.0002843877,0.006252025,0.02589278,0.001543141,0.02656798,0.00005125718,0.0607016,0.0009773962],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995244,0.0001323086,0.001363813,0.0004852033,0.0002077624,0.0002284354,0.00000500734,0.000008241734,0.002325288],"genre_scores_gemma":[0.9817653,0.000003592857,0.01757307,0.0001494513,0.000126214,2.700797e-9,0.000001960303,0.00002560505,0.0003548583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7440746,"threshold_uncertainty_score":0.9635512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01010039091870765,"score_gpt":0.2117722902030708,"score_spread":0.2016718992843632,"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."}}