{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002086689,0.000407624,0.0003367173,0.0004206011,0.0002549291,0.0006502849,0.0004570009,0.0005867592,0.0005124151],"category_scores_gemma":[0.0007258197,0.0001621806,0.0002228715,0.000431773,0.0006263416,0.0004239892,0.0003323247,0.0003089955,0.00008520891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004729324,"about_ca_system_score_gemma":0.0003568327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007597635,"about_ca_topic_score_gemma":0.004107272,"domain_scores_codex":[0.9999009,0.00001379845,0.00001177274,0.00002178732,0.0000325883,0.00001911138],"domain_scores_gemma":[0.9997997,0.00007821664,0.00004794158,0.00003787045,0.00001925017,0.00001703962],"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":[0.00006868444,0.00004974434,0.00374511,0.00005438778,0.00001105754,0.0001701062,0.00005998745,0.9652496,0.02434366,0.001391277,0.00007157025,0.00478475],"study_design_scores_gemma":[0.000008289697,0.00002107506,0.003007581,0.000003190013,0.000002114202,0.0000236488,0.00001661557,0.9942892,0.002031161,0.0003841168,0.0002063823,0.00000661073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9165844,0.0002945234,0.07772825,0.00008127723,0.00003663113,0.0000904697,0.0004729619,0.0002636023,0.004447908],"genre_scores_gemma":[0.9919249,0.0000987774,0.007217934,0.000006803334,0.000005208831,0.00003260046,0.0001302428,0.00001038289,0.0005731994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007597635,"threshold_uncertainty_score":0.0151068,"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."}}