{"id":"W2152126713","doi":"10.1109/icsmc.1995.538147","title":"An expert system to support snow avalanche forecasting","year":2002,"lang":"en","type":"article","venue":"","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"British Columbia Institute of Technology","keywords":"Snow; IBM; Computer science; Expert system; Weather forecasting; Artificial intelligence; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006707081,0.0003919517,0.0003651551,0.000656942,0.0003636504,0.0006547581,0.0006906445,0.0008374446,0.006552652],"category_scores_gemma":[0.002690884,0.0002493038,0.0001946184,0.000549002,0.0001255619,0.0007632344,0.0003757614,0.0005309071,0.00267895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001986485,"about_ca_system_score_gemma":0.0005521768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0032929,"about_ca_topic_score_gemma":0.00451958,"domain_scores_codex":[0.9996818,0.00005526877,0.00004117478,0.00006884229,0.0001313029,0.00002153545],"domain_scores_gemma":[0.9991424,0.0003632912,0.00003320793,0.00007649089,0.0003200226,0.00006452829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004976639,0.0004424333,0.003225317,0.0004224656,0.00008586365,0.001109737,0.0003456288,0.03188471,0.06198082,0.003785109,0.06947187,0.8267483],"study_design_scores_gemma":[0.0005138527,0.0006420109,0.009117238,0.0001705859,0.0002718409,0.001848334,0.0002120405,0.613935,0.06663521,0.00791052,0.2985539,0.0001894856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05086643,0.0008527386,0.8694316,0.0007201954,0.0004707871,0.000653278,0.002427773,0.04790185,0.02667536],"genre_scores_gemma":[0.238424,0.001042889,0.7242169,0.0004528352,0.0001741534,0.0003713895,0.005949753,0.0005048262,0.02886326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006552652,"threshold_uncertainty_score":0.02192086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02487571450262799,"score_gpt":0.2297239782621045,"score_spread":0.2048482637594765,"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."}}