{"id":"W2924506290","doi":"10.1080/24751448.2019.1571843","title":"Learning from Logistics: How Networks Change Our Cities","year":2019,"lang":"en","type":"article","venue":"Technology|Architecture + Design","topic":"Urban Planning and Governance","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Business; Economic geography; Economics","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":[0.002094635,0.0003973438,0.0002026731,0.0007296761,0.005148533,0.0101246,0.0009216553,0.002544903,0.01104262],"category_scores_gemma":[0.005842741,0.0002585188,0.0004182667,0.001286166,0.01159821,0.01926938,0.004884209,0.003281935,0.001817683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007363308,"about_ca_system_score_gemma":0.005728669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02012246,"about_ca_topic_score_gemma":0.03366179,"domain_scores_codex":[0.9986947,0.0007857914,0.00002841874,0.0001221228,0.0001903966,0.000178518],"domain_scores_gemma":[0.9977481,0.0009049012,0.0002920944,0.0002122547,0.0004013557,0.0004412821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002362475,0.00003000382,0.002299423,0.0001465872,0.00001699092,0.0001503897,0.0178709,0.003216722,0.0001774719,0.8452793,0.09090453,0.03988406],"study_design_scores_gemma":[0.00001530954,0.0000210698,0.00250395,0.0002995467,0.00002505124,0.00009364094,0.01980174,0.001665613,0.0004355433,0.4946915,0.480414,0.00003310866],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08136946,0.008735364,0.03005459,0.4809877,0.001810405,0.0000473751,0.0003958642,0.0003821065,0.3962172],"genre_scores_gemma":[0.9299482,0.01016,0.007249581,0.01553414,0.0004710871,0.0000812418,0.0002383909,0.0001733668,0.03614408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02012246,"threshold_uncertainty_score":0.05342478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04721150557480048,"score_gpt":0.2599329348050542,"score_spread":0.2127214292302538,"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."}}