{"id":"W4402540146","doi":"10.1007/978-3-031-61511-5_8","title":"Electrical Conductivity Double Percolation in Portland Cement Mortar Incorporating Iron Sand as Fine Aggregate in Presence of Recycled Carbon Fibers","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Portland cement; Mortar; Materials science; Percolation (cognitive psychology); Aggregate (composite); Electrical resistivity and conductivity; Composite material; Conductivity; Cement; Carbon fibers; Chemistry; Composite number; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002961369,0.0003207301,0.0004202229,0.0003324936,0.00001380963,0.00002248211,0.0001245123,0.0003304803,0.0001646393],"category_scores_gemma":[0.00008368964,0.0003412077,0.00005021599,0.0002470604,0.00005922056,0.000131387,0.0001222792,0.0005299599,0.000004794746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006986654,"about_ca_system_score_gemma":0.00002915697,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004810089,"about_ca_topic_score_gemma":0.0292466,"domain_scores_codex":[0.9983489,0.00001689188,0.0005369624,0.0004997381,0.0003270091,0.0002705192],"domain_scores_gemma":[0.9994339,0.0001162213,0.0001767668,0.0002238024,0.000006370808,0.00004292835],"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":[0.0001752096,0.00003659379,0.09624823,0.0003407785,0.00002752975,0.0001693168,0.0006360231,0.7667462,0.1315016,0.0005996784,0.000004570438,0.003514255],"study_design_scores_gemma":[0.005765059,0.0007947655,0.06090445,0.007451699,0.0002417483,0.0002677023,0.00001420262,0.6451819,0.1982554,0.07589371,0.001188407,0.004040894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913583,0.0003192214,0.0003441526,0.00004240009,0.0004272262,0.0004707263,0.000005548785,0.00004415501,0.006988261],"genre_scores_gemma":[0.999163,0.00003219918,0.0004640301,0.000004705762,0.00006925122,0.00002793869,0.00002617625,0.00005041561,0.0001622888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1215643,"threshold_uncertainty_score":0.999904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008128314892071936,"score_gpt":0.2064985861958378,"score_spread":0.1983702713037658,"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."}}