{"id":"W2581293969","doi":"","title":"An Optimization System on Facilities Placement in Residential Quarter by Genetic Algorithm","year":2008,"lang":"en","type":"article","venue":"ファジィシステムシンポジウム講演論文集","topic":"Facilities and Workplace Management","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Genetic algorithm; Computer science; Algorithm; Mathematical optimization; Mathematics; Machine learning; History","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000253568,0.0003032648,0.0003090662,0.0002490412,0.0001932338,0.00006009342,0.0002950882,0.0001613105,0.002720957],"category_scores_gemma":[0.000006193762,0.0003092649,0.00007896805,0.0002122427,0.0001032297,0.0001298067,0.00004336174,0.0001952222,0.000726654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002554179,"about_ca_system_score_gemma":0.00002457912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001269261,"about_ca_topic_score_gemma":0.00006655313,"domain_scores_codex":[0.9974731,0.0003084326,0.0005442087,0.0006521466,0.0004352739,0.0005868346],"domain_scores_gemma":[0.9989729,0.00005450896,0.00009958824,0.000697927,0.00004011908,0.0001349832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008468488,0.001535666,0.005503566,0.0002037451,0.0002398389,0.0007416718,0.02009827,0.2295908,0.00004390291,0.003198438,0.728273,0.009724235],"study_design_scores_gemma":[0.02514739,0.01056749,0.05946815,0.000669351,0.0002109719,0.0004046269,0.2479205,0.291352,0.0005673117,0.0001772847,0.3581132,0.005401747],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7596815,0.001314073,0.1281632,0.001055907,0.004832546,0.002890307,0.0007021911,0.000896087,0.1004641],"genre_scores_gemma":[0.9491369,0.00005207708,0.003270491,0.0003735557,0.0002696492,0.0003996307,0.0002431968,0.00005931328,0.04619515],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701598,"threshold_uncertainty_score":0.9999359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187032295023957,"score_gpt":0.2448027307025904,"score_spread":0.2329324077523508,"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."}}