{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001966492,0.0001978138,0.0002783036,0.00004569836,0.00008545863,0.00006058049,0.0002588621,0.0001434685,0.0006243889],"category_scores_gemma":[0.00007501693,0.0001708289,0.00007860991,0.0001131293,0.00006552586,0.0001054279,0.003758818,0.0002956826,0.00003273098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001355501,"about_ca_system_score_gemma":0.00002285004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001464555,"about_ca_topic_score_gemma":0.00004164691,"domain_scores_codex":[0.9987022,0.0001149942,0.0003191541,0.00044646,0.0002593773,0.0001578002],"domain_scores_gemma":[0.9992605,0.0002260708,0.0002109578,0.0002337722,0.00002163394,0.00004708],"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":[0.00001469787,0.00008281793,0.1694193,0.0007137738,0.00002377739,0.00000994893,0.002222647,0.62902,0.1526587,0.0002156767,0.0001812038,0.04543739],"study_design_scores_gemma":[0.0002403673,0.0000554805,0.1902362,0.002682545,0.00001791411,0.000001388421,0.00009096297,0.633015,0.1727783,0.0003906201,0.00003485696,0.0004563279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5947035,0.00001350266,0.403653,0.00003630295,0.0003009638,0.0001787548,7.875371e-7,0.00003694888,0.001076264],"genre_scores_gemma":[0.9321066,0.00001098186,0.06753995,0.0001932619,0.00002638939,0.00001052822,0.00003016356,0.00001308376,0.00006908437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3374031,"threshold_uncertainty_score":0.69662,"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."}}