{"id":"W2091126394","doi":"10.1016/j.geomorph.2007.08.012","title":"Replication of a terrain stability mapping using an Artificial Neural Network","year":2007,"lang":"en","type":"article","venue":"Geomorphology","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Terrain; Artificial neural network; Learning vector quantization; Vector quantization; Geology; Artificial intelligence; Computer science; Remote sensing; Data mining; Cartography; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.00113298,0.00006824809,0.0001211511,0.00001740636,0.00008843422,0.000004534422,0.0001194707,0.0001119464,0.001322967],"category_scores_gemma":[0.00003087975,0.00005808476,0.00004196277,0.0001836816,0.0002081025,0.00006643008,0.00008583227,0.0001083766,0.00002484774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005944943,"about_ca_system_score_gemma":0.000005913807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006681678,"about_ca_topic_score_gemma":0.000376847,"domain_scores_codex":[0.9989884,0.00006408972,0.0002732442,0.0002947274,0.00009766687,0.0002818669],"domain_scores_gemma":[0.9993777,0.0000305993,0.0001156792,0.0004073256,0.000007907825,0.00006073077],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001910574,0.0002239618,0.2706985,0.000008181179,0.00001851632,0.00004307311,0.001702077,0.02990272,0.6656579,0.0001677032,0.0004331153,0.03095319],"study_design_scores_gemma":[0.000864188,0.0005907295,0.861941,0.00002012321,0.00007100861,0.0004952216,0.001040251,0.08342208,0.03380062,0.007518149,0.009621912,0.0006147496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992395,0.0000144585,0.006495195,0.00008278685,0.0002006652,0.0001166881,0.000004287575,0.00002014016,0.000670725],"genre_scores_gemma":[0.9975777,0.00000112192,0.002152035,0.0001357193,0.000086382,0.000001174514,0.0000256645,0.00000633709,0.00001387535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6318573,"threshold_uncertainty_score":0.99959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065540726044532,"score_gpt":0.2730453934650072,"score_spread":0.2323899862045619,"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."}}