{"id":"W2948828813","doi":"10.3390/pr7060346","title":"Numerical Determination of RVE for Heterogeneous Geomaterials Based on Digital Image Processing Technology","year":2019,"lang":"en","type":"article","venue":"Processes","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Higher Education Discipline Innovation Project; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Representative elementary volume; Cohesion (chemistry); Materials science; Digital image; Sample size determination; Digital image processing; Image processing; Compressive strength; Biological system; Composite material; Microstructure; Image (mathematics); Mathematics; Computer science; Statistics; Artificial intelligence; Physics","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":[0.0005696442,0.0004744747,0.0003432044,0.001705381,0.0001669196,0.0005289647,0.0006352394,0.0005391273,0.0007567432],"category_scores_gemma":[0.002364095,0.0002720114,0.0003479432,0.0009774747,0.000462998,0.0008299809,0.0003996626,0.0003881668,0.0002146561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003273858,"about_ca_system_score_gemma":0.0003509796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190795,"about_ca_topic_score_gemma":0.001505545,"domain_scores_codex":[0.9996212,0.00005066838,0.0000271169,0.00008903778,0.0001901437,0.00002177248],"domain_scores_gemma":[0.9992374,0.0003514343,0.0001059102,0.0001070376,0.0001811731,0.00001707844],"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":[0.0001419008,0.0001222882,0.009279356,0.0005057991,0.00006835521,0.0002785831,0.0003395023,0.3292885,0.3005441,0.0122509,0.0009522914,0.3462284],"study_design_scores_gemma":[0.000006559112,0.00003704215,0.002922026,0.000009433041,0.00001550521,0.0001313813,0.0000347311,0.9481046,0.04629387,0.001480608,0.0009381215,0.00002605649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03849504,0.0001090203,0.9600043,0.00003012556,0.000009954851,0.00003541135,0.00006508778,0.0004612328,0.0007896843],"genre_scores_gemma":[0.3683821,0.000170074,0.6305134,0.00002540352,0.000009669067,0.0001073329,0.0001928237,0.00007908294,0.0005201172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705381,"threshold_uncertainty_score":0.003012598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007942697634571323,"score_gpt":0.2284610271667301,"score_spread":0.2205183295321588,"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."}}