{"id":"W2154066755","doi":"10.1680/geot.13.p.208","title":"Physical and numerical modelling of dry granular flows under Coriolis conditions","year":2015,"lang":"en","type":"article","venue":"Géotechnique","topic":"Landslides and related hazards","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Centrifuge; Mechanics; Acceleration; Rheology; Geology; Magnitude (astronomy); Geotechnical engineering; Flow (mathematics); Granular material; Physics; Classical mechanics; Thermodynamics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001057575,0.00007669876,0.0001271197,0.00001723309,0.00004477194,0.000007132913,0.00007549266,0.00009370565,0.00006564926],"category_scores_gemma":[0.000005064236,0.00005879605,0.00003776323,0.0001145898,0.0001222065,0.00007509603,0.00008074911,0.0001420529,0.00002808621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003727437,"about_ca_system_score_gemma":0.000009159185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003117982,"about_ca_topic_score_gemma":0.000004618529,"domain_scores_codex":[0.9994487,0.00002507996,0.0001025766,0.0001474635,0.0001505061,0.0001256576],"domain_scores_gemma":[0.9997055,0.00001709482,0.00003347244,0.0001306518,0.000007517694,0.0001057832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001315977,0.0007747132,0.01717408,0.00003653337,0.00007179767,0.00005227248,0.003389581,0.8955055,0.05242889,0.01664809,0.007499737,0.006287148],"study_design_scores_gemma":[0.0007426481,0.0003031657,0.002461499,0.00004433431,0.00006782787,0.00002931007,0.0001242813,0.8383183,0.0259178,0.1243996,0.007166743,0.0004244339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5822784,0.00002296704,0.4143816,0.000153193,0.00003283058,0.0001264303,0.000009933931,0.00006020674,0.002934475],"genre_scores_gemma":[0.9936983,0.0000200929,0.006082199,0.00006482137,0.00002541875,0.00001092635,0.000007052503,0.000009141491,0.00008206543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4114199,"threshold_uncertainty_score":0.2397633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957652258510871,"score_gpt":0.2407683275775881,"score_spread":0.2211918049924794,"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."}}