{"id":"W4406825428","doi":"10.18280/mmep.120115","title":"Direct Shear of Self-Consolidating Concrete and Conventional Concrete with Different Coarse Aggregate Size","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Innovations in Concrete and Construction Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Self-consolidating concrete; Aggregate (composite); Materials science; Composite material; Geotechnical engineering; Shear (geology); Geology; Compressive strength","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000195449,0.0002061312,0.0003833552,0.0000957521,0.00006162959,0.00006323659,0.00005965667,0.00008625505,0.00002056374],"category_scores_gemma":[0.00003036316,0.0001772193,0.00003009985,0.0001382738,0.00008105318,0.0000784725,0.00003143443,0.0001289756,0.000001025304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001759287,"about_ca_system_score_gemma":0.00001209285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002627443,"about_ca_topic_score_gemma":5.150381e-8,"domain_scores_codex":[0.9990652,0.00001338407,0.000424533,0.0001785545,0.0001132144,0.0002050992],"domain_scores_gemma":[0.9994147,0.0002808769,0.00004933755,0.0001388914,0.00006540559,0.00005076496],"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":[0.000057597,0.00001141337,0.0002440327,0.01338968,0.001155621,0.000007653389,0.001340982,0.6313733,0.07512363,0.2757869,0.0000649108,0.001444287],"study_design_scores_gemma":[0.0004841576,0.00003271284,0.000008083221,0.0009945473,0.00007255769,0.00002196012,0.00003557148,0.9806691,0.01558373,0.00171766,0.0001692123,0.0002106662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7295691,0.0002935172,0.2681912,0.00002321425,0.0001075219,0.0001934014,0.00001184337,0.0002813673,0.001328825],"genre_scores_gemma":[0.9408595,0.0001219511,0.05885107,0.0000102074,0.00002095004,0.00004355864,0.000003848445,0.00002685358,0.00006203459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3492959,"threshold_uncertainty_score":0.7226793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00939615744541975,"score_gpt":0.1957310636738596,"score_spread":0.1863349062284398,"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."}}