{"id":"W3191587271","doi":"","title":"Infrastructural architecture: social design for the public realm in underground transit systems","year":2019,"lang":"en","type":"dissertation","venue":"Lu Zone Ul (Laurentian University)","topic":"Underground infrastructure and sustainability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Realm; Architecture; Public transport; Transit (satellite); Transit system; Urban design; Architectural engineering; Engineering; Political science; Transport engineering; Geography; Archaeology; Law","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"],"consensus_categories":[],"category_scores_codex":[0.0001985269,0.0005389136,0.0005924484,0.0006803636,0.0003447319,0.0002479722,0.0007223102,0.0006715232,0.00009427789],"category_scores_gemma":[0.00002120676,0.0005034724,0.0003229832,0.0007909869,0.00009517927,0.0003566005,0.00002575562,0.000867347,0.000004837341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007806586,"about_ca_system_score_gemma":0.0003148514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001550904,"about_ca_topic_score_gemma":0.006172325,"domain_scores_codex":[0.9979438,0.0001652215,0.0003796622,0.0004961356,0.0003223317,0.000692808],"domain_scores_gemma":[0.9988995,0.0002760589,0.0001404933,0.000422018,0.0001626714,0.00009925762],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003642944,0.0003163055,0.0009472866,0.01662706,0.006317045,0.0003380051,0.05891879,0.5575091,0.002108471,0.2221966,0.04074739,0.09033106],"study_design_scores_gemma":[0.01227634,0.0006802622,0.01480301,0.0006077699,0.002701117,0.00009924733,0.2915277,0.08047463,0.0003684293,0.02078369,0.5692242,0.00645349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0884844,0.001894261,0.8787014,0.0005461167,0.008345481,0.00539975,0.0001979406,0.0006748601,0.01575583],"genre_scores_gemma":[0.9902264,0.00007274862,0.0002928083,0.00001587959,0.0002667766,0.00001418875,0.0009560208,0.000101029,0.008054161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.901742,"threshold_uncertainty_score":0.9997417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009660989689316815,"score_gpt":0.1965917821065414,"score_spread":0.1869307924172245,"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."}}