{"id":"W1974683201","doi":"10.1139/l04-003","title":"Numerical assessment and prediction method for the chemico-mechanical deterioration of ASR-affected concrete structures","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Concrete Corrosion and Durability","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Durability; Alkali–silica reaction; Bridge (graph theory); Structural engineering; Finite element method; Credibility; Suspension (topology); Computer science; Inverse; Inverse problem; Engineering; Materials science; Mathematics; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000880248,0.0005022374,0.0003975267,0.0003777292,0.0003290589,0.0004781911,0.0009295124,0.00103774,0.001742899],"category_scores_gemma":[0.001825569,0.000263412,0.0005438487,0.0002182373,0.0005357215,0.0004670495,0.0005047519,0.0007768065,0.0003563419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004752412,"about_ca_system_score_gemma":0.0008991105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003190764,"about_ca_topic_score_gemma":0.002455024,"domain_scores_codex":[0.9996309,0.0001016274,0.00002083567,0.00005832941,0.00017317,0.00001507042],"domain_scores_gemma":[0.9995635,0.0001883851,0.00004444749,0.00004193885,0.0001431461,0.00001864454],"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":[0.00005547266,0.00007895045,0.001415799,0.0001003997,0.00002201241,0.00009852115,0.0001452057,0.9031056,0.03118893,0.009638609,0.0004754862,0.05367502],"study_design_scores_gemma":[0.000003662367,0.00002395696,0.00009112468,0.000002006467,0.000002847818,0.00001735639,0.000005166061,0.9972647,0.001851495,0.0004427359,0.0002903566,0.000004548884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01258439,0.00003373405,0.9858907,0.00005055212,0.00001974517,0.00003861602,0.00001463086,0.0001466501,0.001221012],"genre_scores_gemma":[0.4854675,0.00015723,0.5104488,0.00003003304,0.00002488089,0.0003224439,0.00006114739,0.00006057989,0.003427337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003190764,"threshold_uncertainty_score":0.006344378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009102532025680982,"score_gpt":0.2361335285101863,"score_spread":0.2270309964845054,"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."}}