{"id":"W4235395575","doi":"10.32920/ryerson.14655576","title":"Computer simulation of developing erosion profiles including interference effects","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Erosion and Abrasive Machining","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Erosion; Interference (communication); Abrasive; Particle (ecology); Materials science; Jet (fluid); Substrate (aquarium); Mechanics; Tracking (education); Function (biology); Particle size; Computer science; Composite material; Engineering; Geology; Physics; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000185622,0.0003395647,0.0004654499,0.0003007092,0.0003633921,0.0006120029,0.0006680867,0.0008736107,0.002072404],"category_scores_gemma":[0.001326311,0.0003295009,0.000342049,0.0004724875,0.0004502604,0.0004532993,0.0002803596,0.0004739101,0.0002086229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006079354,"about_ca_system_score_gemma":0.0008601025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00935741,"about_ca_topic_score_gemma":0.003884714,"domain_scores_codex":[0.9999049,0.000015913,0.000004826384,0.00001779986,0.00003646349,0.00002017398],"domain_scores_gemma":[0.9994136,0.0003305753,0.00003626345,0.00004734615,0.0001408114,0.00003149932],"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":[0.00002648426,0.00001900714,0.0005703435,0.00001418165,0.000004789251,0.00005265357,0.00003220619,0.9937478,0.002721664,0.001277395,0.00008671921,0.001446761],"study_design_scores_gemma":[0.000006807512,0.000008280283,0.0001287081,0.000001145617,0.000001580853,0.000007849797,0.000003863509,0.9987859,0.0007196142,0.0001670496,0.000167143,0.000002121766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7713551,0.0001465916,0.2046274,0.0001783369,0.00004833184,0.0001261518,0.0005768525,0.0009417374,0.02199937],"genre_scores_gemma":[0.9675907,0.0001085395,0.02777907,0.00002399261,0.000004807275,0.0001331741,0.0002973427,0.00007886556,0.003983514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00935741,"threshold_uncertainty_score":0.01860589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04208892913134361,"score_gpt":0.3055376910076285,"score_spread":0.2634487618762849,"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."}}