{"id":"W4400235025","doi":"10.11159/iccste24.171","title":"Life Cycle Analysis of Light Weight Artificial Aggregates for Sustainable Construction","year":2024,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"BIM and Construction Integration","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001027625,0.0004484201,0.0003578374,0.0006654321,0.0002332123,0.0006384666,0.0002946937,0.0003373364,0.0008213538],"category_scores_gemma":[0.0007850201,0.0001324553,0.0006989654,0.0006260182,0.0002015719,0.0004060759,0.0002638552,0.0002192777,0.0001342013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385063,"about_ca_system_score_gemma":0.00077082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003759834,"about_ca_topic_score_gemma":0.004861857,"domain_scores_codex":[0.9997051,0.00007896726,0.0000162683,0.00003755643,0.0001274067,0.00003454644],"domain_scores_gemma":[0.9996705,0.0001434649,0.00005969509,0.00002459247,0.00008876637,0.00001297014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004690561,0.00028297,0.01677252,0.0003107764,0.00007806956,0.0001371251,0.00007484084,0.8257389,0.1132359,0.00307027,0.0001823385,0.03964733],"study_design_scores_gemma":[0.00002361732,0.001682661,0.01678638,0.00002746158,0.0001047657,0.00004898096,0.0001625003,0.8758799,0.09966618,0.002492502,0.003089729,0.00003530286],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720296,0.000608286,0.02390146,0.00003191844,0.000007353006,0.0001228097,0.0006108601,0.00003727682,0.002650386],"genre_scores_gemma":[0.9935135,0.000302435,0.005106391,0.000005198806,0.000001056564,0.00008161132,0.0003971047,0.000006352251,0.0005864089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003759834,"threshold_uncertainty_score":0.0100494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008083448909523405,"score_gpt":0.2096009281644817,"score_spread":0.2015174792549583,"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."}}