{"id":"W2904168922","doi":"10.1155/2018/4647675","title":"Prediction of Settling Velocity of Nonspherical Soil Particles Using Digital Image Processing","year":2018,"lang":"en","type":"article","venue":"Advances in Civil Engineering","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministry for Food, Agriculture, Forestry and Fisheries; National Research Foundation of Korea; Ministry of Education; National Research Foundation","keywords":"Settling; Calipers; Shape factor; Digital image; Particle (ecology); Mathematics; Digital image processing; Particle size; Geology; Displacement (psychology); Materials science; Mineralogy; Image processing; Geotechnical engineering; Optics; Geometry; Image (mathematics); Physics; Computer science; Artificial intelligence","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":[0.0004506086,0.0005150008,0.000530184,0.002519305,0.0001786634,0.0006708296,0.0003683648,0.0005507804,0.0009499286],"category_scores_gemma":[0.001171179,0.0002126139,0.0005352494,0.001965375,0.0001386726,0.0004124581,0.000188661,0.0002981889,0.0005735988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005029706,"about_ca_system_score_gemma":0.0003637787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006304247,"about_ca_topic_score_gemma":0.006204825,"domain_scores_codex":[0.9997694,0.00001442879,0.00001828265,0.00006826142,0.0001026472,0.00002704776],"domain_scores_gemma":[0.9995267,0.0001337262,0.0000787261,0.00002743327,0.0002023737,0.00003101046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008113172,0.0004481156,0.1106083,0.000629047,0.0001144962,0.0004482165,0.0002602039,0.05070199,0.3960582,0.0008957318,0.001732741,0.4372918],"study_design_scores_gemma":[0.00002789407,0.0002288309,0.145676,0.00002167636,0.00006127762,0.0001771094,0.0000946391,0.7688121,0.0831373,0.000395799,0.001306874,0.000060523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.754094,0.0005821714,0.2393092,0.00003937201,0.00005530058,0.0002286044,0.001069545,0.001753342,0.002868446],"genre_scores_gemma":[0.8493633,0.0003696097,0.1466355,0.0000207706,0.00001181973,0.0001550356,0.001355303,0.00009233494,0.001996283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006304247,"threshold_uncertainty_score":0.0125351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01727634110903109,"score_gpt":0.2214531762998505,"score_spread":0.2041768351908194,"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."}}