{"id":"W3195675931","doi":"10.3390/f12081087","title":"A Comparison of an Adaptive Neuro-Fuzzy and Frequency Ratio Model to Landslide-Susceptibility Mapping along Forest Road Networks","year":2021,"lang":"en","type":"article","venue":"Forests","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia","funders":"Iran National Science Foundation; National Science Foundation","keywords":"Landslide; Adaptive neuro fuzzy inference system; Geographic information system; Computer science; Geology; Data mining; Cartography; Fuzzy logic; Remote sensing; Geography; Artificial intelligence; Geotechnical engineering; Fuzzy control system","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0001852321,0.0001522933,0.0002615374,0.00002584235,0.0001244218,0.00003517645,0.0001482838,0.0001183886,0.00009540639],"category_scores_gemma":[0.00005190913,0.0001264973,0.0000536872,0.0002419051,0.00009559916,0.0002140837,0.000215468,0.000187555,0.0000146823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005307622,"about_ca_system_score_gemma":0.00002419007,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008691055,"about_ca_topic_score_gemma":0.03354655,"domain_scores_codex":[0.9986805,0.00006418834,0.0003233698,0.0004180461,0.0002280135,0.0002858715],"domain_scores_gemma":[0.9993104,0.00003979139,0.00009095939,0.0003319907,0.00002466385,0.0002021586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003011179,0.00007076973,0.6176266,0.000005648245,0.000009390623,0.00001453991,0.0007023064,0.376427,0.0007873717,0.000163809,0.000216738,0.003945733],"study_design_scores_gemma":[0.0002101511,0.0001428676,0.5180701,0.00002087722,0.0000119016,0.000007395649,0.0001041211,0.479757,0.0001517985,0.001372589,0.00003557222,0.0001157088],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9725088,0.0001018816,0.02513841,0.00009589593,0.00008406555,0.0002174675,0.00001109962,0.00002845287,0.001813865],"genre_scores_gemma":[0.9937627,0.00001016496,0.005936038,0.0001070964,0.00003688461,0.00001064752,0.00002759613,0.00001535627,0.00009348054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.10333,"threshold_uncertainty_score":0.9840887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468509748078927,"score_gpt":0.2691315234123271,"score_spread":0.2444464259315378,"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."}}