{"id":"W2753069064","doi":"","title":"Optimization of Aggregate Gradation Combinations to Improve Concrete Sustainability","year":2011,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Asphalt Pavement Performance Evaluation","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gradation; Aggregate (composite); Durability; Sustainability; Cement; Materials science; Civil engineering; Engineering; Waste management; Process engineering; Computer science; Composite material","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00002040071,0.0002156813,0.0002744729,0.00006272265,0.0000790925,0.0000112145,0.0001611029,0.00005606022,0.00004768272],"category_scores_gemma":[0.00001017509,0.0002465976,0.00002629991,0.0001246371,0.0000238112,0.0004306606,0.00003010991,0.0001224384,2.455509e-9],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003071872,"about_ca_system_score_gemma":0.001195005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001190301,"about_ca_topic_score_gemma":0.00958847,"domain_scores_codex":[0.9980568,0.00003404055,0.0004663389,0.0001966354,0.001045738,0.0002004298],"domain_scores_gemma":[0.9993313,0.00007129096,0.0002512731,0.0002079703,0.000006198648,0.0001319635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00298162,0.0001512386,0.01642792,0.02172282,0.001391375,0.00003195899,0.005396751,0.4984501,0.1306489,0.1880747,0.003055032,0.1316675],"study_design_scores_gemma":[0.0009611108,0.0002551597,0.03045148,0.0004770469,0.0001618652,6.912091e-7,0.006208828,0.2769512,0.6803928,0.001878449,0.001481405,0.0007799211],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7640314,0.0004450518,0.004945761,0.0004846075,0.001760939,0.002198609,0.0007268071,0.00008040469,0.2253265],"genre_scores_gemma":[0.9914659,0.000160715,0.001576441,0.0000547726,0.00002560939,0.0000497262,0.000443365,0.00004061287,0.006182866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5497439,"threshold_uncertainty_score":0.9999986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00300612200468687,"score_gpt":0.1603353935787683,"score_spread":0.1573292715740815,"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."}}