{"id":"W1978116127","doi":"10.4028/www.scientific.net/amr.89-91.29","title":"A Markov Chain Fracture Model for Intergranular Crack Propagation in Polycrystalline Materials","year":2010,"lang":"en","type":"article","venue":"Advanced materials research","topic":"Fatigue and fracture mechanics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Nucleation; Materials science; Coalescence (physics); Voronoi diagram; Intergranular corrosion; Grain boundary; Fracture mechanics; Markov chain; Microstructure; Monte Carlo method; Void (composites); Intergranular fracture; Mechanics; Structural engineering; Statistical physics; Composite material; Geometry; Mathematics; Engineering; Physics; Thermodynamics","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":[0.0005424258,0.0005337571,0.0009945035,0.0006788387,0.0006325072,0.000859594,0.002076649,0.00184322,0.002704985],"category_scores_gemma":[0.001213636,0.0004966811,0.0009867888,0.0008326859,0.001058612,0.001272598,0.0004204786,0.001033279,0.0004103024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001113918,"about_ca_system_score_gemma":0.001111352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01243213,"about_ca_topic_score_gemma":0.008171816,"domain_scores_codex":[0.9997336,0.0000584499,0.00001406783,0.00005117488,0.00009781199,0.00004480339],"domain_scores_gemma":[0.9993536,0.0003726962,0.00008823175,0.00003987295,0.000115657,0.00002993635],"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":[0.00001571458,0.00001511318,0.0003544962,0.00002939416,0.00001250561,0.0001172116,0.0000265145,0.9624192,0.001395526,0.03274544,0.0002306859,0.002638308],"study_design_scores_gemma":[0.000005279084,0.000008295649,0.00007563276,0.000002599853,0.00000340495,0.00002823412,0.000002461547,0.99318,0.0001564012,0.006295276,0.0002369158,0.000005404737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03629532,0.0005836801,0.9597216,0.0002731511,0.00005344701,0.00006469643,0.000319783,0.0002048689,0.0024835],"genre_scores_gemma":[0.8387244,0.001620577,0.1462194,0.0001278614,0.00009166846,0.0006089215,0.0006825647,0.000140987,0.01178357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01243213,"threshold_uncertainty_score":0.02471954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02236110127738644,"score_gpt":0.3147952182501718,"score_spread":0.2924341169727854,"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."}}