{"id":"W3153199766","doi":"10.5267/j.esm.2021.3.003","title":"Fracture resistance of railway ballast rock under tensile and tear loads","year":2021,"lang":"en","type":"article","venue":"Engineering Solid Mechanics","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Waterloo","funders":"","keywords":"Tearing; Materials science; Ultimate tensile strength; Composite material; Fracture (geology); Fracture toughness; Enhanced Data Rates for GSM Evolution; Fracture mechanics; Tensile testing; Deformation (meteorology); Toughness; Ballast; Structural engineering; Geology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001221437,0.0002253603,0.0003523426,0.00009166953,0.00004302034,0.00002804051,0.00009901495,0.000167764,0.0000272663],"category_scores_gemma":[0.00007210155,0.0002536425,0.00008196336,0.0001963257,0.000001854076,0.00008363095,0.00006157015,0.0002648793,0.000005346616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004446538,"about_ca_system_score_gemma":0.00003566752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001261856,"about_ca_topic_score_gemma":0.000007000362,"domain_scores_codex":[0.9989502,0.000008241284,0.0003016522,0.0002350272,0.0001888117,0.0003160781],"domain_scores_gemma":[0.9993777,0.00006282136,0.00003601454,0.0003094002,0.0001016108,0.000112434],"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":[0.000002690012,0.000008726963,4.31796e-7,0.0002156973,0.00005538434,0.00001208681,0.00011398,0.8246746,0.1689432,0.005358757,0.0004946051,0.0001198844],"study_design_scores_gemma":[0.0001749811,0.000009709941,0.000006863993,0.0001736096,0.0000259604,0.00001948737,0.00008477554,0.7865481,0.2019087,0.0007282484,0.01005063,0.0002688311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02926847,0.004810666,0.9646485,0.00008291489,0.0006398652,0.00009063174,0.00001529903,0.0002949893,0.0001486714],"genre_scores_gemma":[0.9918467,0.0007633058,0.006904225,0.00006990157,0.000105374,0.000007563683,0.00001068039,0.00008701249,0.0002052622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9625782,"threshold_uncertainty_score":0.9999916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00566455412241244,"score_gpt":0.1903076693698431,"score_spread":0.1846431152474306,"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."}}