{"id":"W7031792089","doi":"","title":"Snow avalanches","year":2004,"lang":"en","type":"article","venue":"DORA WSL (Swiss Federal Institute for Forest, Snow and Landscape Research)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Snow; Recreation; Snow removal; Hazard; Natural hazard; Natural disaster","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000312516,0.0009574713,0.0006612032,0.001529641,0.001174201,0.001706765,0.0004312213,0.0008309456,0.01593598],"category_scores_gemma":[0.001021394,0.0002550395,0.0008979205,0.001485345,0.0005068149,0.0008939208,0.001661608,0.0007501753,0.004211098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008920676,"about_ca_system_score_gemma":0.0008819809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005252135,"about_ca_topic_score_gemma":0.006752309,"domain_scores_codex":[0.9994681,0.00004301323,0.00005248149,0.00009893416,0.0002215125,0.0001159754],"domain_scores_gemma":[0.9994476,0.00006526399,0.0002037551,0.00004208679,0.0001279713,0.0001133318],"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":[0.001430013,0.001016793,0.1202568,0.006793682,0.0007093172,0.009400162,0.001654292,0.006324493,0.03770565,0.02364339,0.1399745,0.6510909],"study_design_scores_gemma":[0.0002544271,0.001703932,0.2924263,0.002956315,0.0003964868,0.02444972,0.001495678,0.004298159,0.01092798,0.02669401,0.6342534,0.0001435634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4732254,0.08660423,0.03976331,0.002760128,0.00343266,0.003786584,0.02364084,0.003879902,0.3629069],"genre_scores_gemma":[0.8577819,0.03874599,0.007469596,0.001382842,0.0008166867,0.0005721197,0.0129432,0.0001953109,0.08009227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01593598,"threshold_uncertainty_score":0.05331117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03939426469745453,"score_gpt":0.2930041526325328,"score_spread":0.2536098879350782,"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."}}