{"id":"W3142666957","doi":"10.1109/wsc.2007.4419839","title":"Construction noise prediction and barrier optimization using special purpose simulation","year":2007,"lang":"en","type":"article","venue":"2007 Winter Simulation Conference","topic":"BIM and Construction Integration","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Noise barrier; Noise (video); Noise control; Plan (archaeology); Computer science; Simulation software; Software; Point (geometry); Noise pollution; Control (management); Simulation modeling; Roadway noise; Systems engineering; Simulation; Industrial engineering; Construction engineering; Transport engineering; Engineering; Noise reduction; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004541401,0.0007110782,0.0007439258,0.0006103619,0.0004114487,0.0007961857,0.0008565533,0.001030202,0.002293919],"category_scores_gemma":[0.001148902,0.0005305469,0.001018511,0.0006158518,0.0005188113,0.0004475718,0.0006837333,0.0004315607,0.0002758947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006515054,"about_ca_system_score_gemma":0.0009645467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01786071,"about_ca_topic_score_gemma":0.01086448,"domain_scores_codex":[0.9996884,0.0001379275,0.00001373461,0.00003257705,0.00008003105,0.00004739721],"domain_scores_gemma":[0.9994451,0.0002904646,0.0000563137,0.0000500013,0.0001178592,0.00004024175],"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":[0.00001388344,0.000007391069,0.0003268009,0.000005789147,0.000004480781,0.00001248299,0.00000754405,0.998042,0.0003295299,0.000332003,0.00003462818,0.0008834115],"study_design_scores_gemma":[0.000002762048,0.000006218344,0.00006814262,9.715696e-7,0.000001897458,0.000002699283,0.000003285671,0.999464,0.0002248223,0.0001356702,0.00008814006,0.000001433201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3592922,0.0001248213,0.6209579,0.000134103,0.00005005931,0.00007258914,0.0002601628,0.001377922,0.01773018],"genre_scores_gemma":[0.9655896,0.0001002833,0.03146353,0.00001490266,0.000006469083,0.0000905193,0.0002064685,0.0001056638,0.002422509],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01786071,"threshold_uncertainty_score":0.03551352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01777994714528297,"score_gpt":0.2453138755798394,"score_spread":0.2275339284345565,"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."}}