{"id":"W4406616395","doi":"10.1016/j.rineng.2025.104087","title":"Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning","year":2025,"lang":"en","type":"article","venue":"Results in Engineering","topic":"Recycled Aggregate Concrete Performance","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services","funders":"","keywords":"Galvanization; Aggregate (composite); Materials science; Bond; Composite material; Fiber; Structural engineering; Engineering; Layer (electronics); Business","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":[0.0001968227,0.0002783365,0.0003802085,0.0003562161,0.00004208146,0.00002801674,0.0001135884,0.0001485628,0.00000311081],"category_scores_gemma":[0.00007737651,0.0002824496,0.00003736441,0.0004295426,0.00004133027,0.000291574,0.00005357573,0.0004363963,6.761878e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001498912,"about_ca_system_score_gemma":0.00002895317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006973945,"about_ca_topic_score_gemma":0.00000720805,"domain_scores_codex":[0.9986628,0.00001426996,0.0005566221,0.0002620855,0.000168155,0.0003360393],"domain_scores_gemma":[0.9994615,0.00008058386,0.00009305128,0.0002508631,0.00004651833,0.00006746699],"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":[0.0002039407,8.202102e-7,0.0004035554,0.0002557607,0.00002538927,0.00001122728,0.0001850066,0.8962614,0.1011702,0.00002794509,0.000004263867,0.001450518],"study_design_scores_gemma":[0.002460691,0.00004751843,0.0001901019,0.0009693566,0.00005185795,0.00001829226,0.00001781789,0.9498472,0.0460534,0.000001438818,0.0001069629,0.0002354067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879263,0.000720087,0.009682708,0.000007603397,0.0001130491,0.0002944822,0.00003802058,0.000312882,0.0009048714],"genre_scores_gemma":[0.986953,0.0004912883,0.01212645,0.000003137468,0.0000197589,0.00003030885,0.00003248012,0.00006076217,0.0002828816],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05511676,"threshold_uncertainty_score":0.9999627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006807935752582803,"score_gpt":0.2062154068999562,"score_spread":0.1994074711473734,"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."}}