{"id":"W27352134","doi":"10.1371/journal.pone.0157902","title":"Green Infrastructure.A math model for optimizing economic and sustainable public investments in the urban area","year":2013,"lang":"en","type":"dissertation","venue":"PLoS ONE","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre for Blood Research, University of British Columbia; KWF Kankerbestrijding; Michael Smith Health Research BC","keywords":"Computer science; Simulated annealing; Sustainability; Reuse; Originality; Competence (human resources); Knapsack problem; Mathematical optimization; Management science; Operations research; Engineering; Mathematics; Machine learning; Economics; Algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002780212,0.0005412339,0.0002475761,0.0007221493,0.0005464553,0.001500466,0.0005406206,0.0007966305,0.01342179],"category_scores_gemma":[0.00053794,0.0002093199,0.0005657066,0.0008645896,0.0006517196,0.001571732,0.0008793196,0.0008036814,0.001215481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002438228,"about_ca_system_score_gemma":0.00213894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01096976,"about_ca_topic_score_gemma":0.02429548,"domain_scores_codex":[0.9998796,0.00004455935,0.00000365905,0.00002576744,0.00002324345,0.00002317689],"domain_scores_gemma":[0.999881,0.00003485854,0.00002234336,0.00001059706,0.00002001112,0.00003117347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002758199,0.00005633083,0.001006868,0.00006282433,0.00002133506,0.00008037209,0.00009769661,0.253869,0.0007388652,0.7102317,0.009738267,0.0240692],"study_design_scores_gemma":[0.00003366182,0.00008214645,0.001526566,0.00008964508,0.00003707853,0.00007223822,0.0006072727,0.425141,0.0006380685,0.4685585,0.1031733,0.00004051984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0961346,0.001807276,0.4744084,0.01962533,0.0005154385,0.000280357,0.004679843,0.0008360958,0.4017127],"genre_scores_gemma":[0.8002325,0.0024515,0.09606046,0.000347439,0.00009809739,0.0003913413,0.0007494291,0.0002125054,0.09945684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01342179,"threshold_uncertainty_score":0.0449003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04065871249818199,"score_gpt":0.2551945696948257,"score_spread":0.2145358571966437,"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."}}