{"id":"W2528227303","doi":"10.1016/j.conbuildmat.2016.09.125","title":"Self-healing and expansion characteristics of cementitious composites with high volume fly ash and MgO-type expansive agent","year":2016,"lang":"en","type":"article","venue":"Construction and Building Materials","topic":"Concrete and Cement Materials Research","field":"Engineering","cited_by":126,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"Division of Electrical, Communications and Cyber Systems; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Durability; Composite material; Fly ash; Compressive strength; Cement; Self-healing; Expansive; Scanning electron microscope; Cementitious; Microstructure; Ductility (Earth science); Composite number; Autoclave; Metallurgy; Creep","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001589527,0.0001926124,0.0001193047,0.0003112463,0.0001165697,0.0001142395,0.0001285047,0.0001786235,0.0009934609],"category_scores_gemma":[0.0002424131,0.0001551074,0.0001764599,0.0001943487,0.0001989461,0.0002445977,0.00009536024,0.0002369947,0.0001141221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001008733,"about_ca_system_score_gemma":0.0000956028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006077621,"about_ca_topic_score_gemma":0.001216522,"domain_scores_codex":[0.9998945,0.000009492597,0.000006754357,0.00002048999,0.0000428442,0.00002597604],"domain_scores_gemma":[0.9997138,0.00007197934,0.00008643685,0.0000174321,0.00006146688,0.00004887559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001940103,0.00001927563,0.0003809572,0.00002082514,0.000003023521,0.00004054591,0.00004224556,0.0002129568,0.9982028,0.00005818612,0.0000147399,0.0008105859],"study_design_scores_gemma":[0.000006722215,0.0001980724,0.006781017,0.000002358554,0.00001240761,0.00004920008,0.00003615605,0.002040331,0.990562,0.00001712438,0.0002883473,0.000006328658],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998993,0.0002050332,0.0003734133,0.000004713886,0.000005557716,0.000002747347,0.0000305287,0.00001382795,0.0003711818],"genre_scores_gemma":[0.9991818,0.00006310232,0.0002127751,0.000003432518,0.000002095351,0.000002873536,0.00003552866,0.000005171956,0.0004930819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009934609,"threshold_uncertainty_score":0.003323436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007441922638013802,"score_gpt":0.2101712075259258,"score_spread":0.202729284887912,"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."}}