{"id":"W7096005827","doi":"","title":"Whose street is it anyway? Regaining lost ground for pedestrians","year":2015,"lang":"en","type":"article","venue":"","topic":"Urban Design and Spatial Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Infill; Pedestrian; Architecture; Heading (navigation); Public housing; Space (punctuation); Urban planning; Domain (mathematical analysis)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001399821,0.0001263932,0.0001749239,0.00007409044,0.00003328025,0.00006115086,0.0001170035,0.00006635209,0.0002690993],"category_scores_gemma":[0.00003939284,0.0001142973,0.00008974898,0.0001609945,0.00001319472,0.000133363,0.00001374718,0.00006092158,0.0001451131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005305418,"about_ca_system_score_gemma":0.00002193309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002974844,"about_ca_topic_score_gemma":0.0007054948,"domain_scores_codex":[0.9993236,0.000009186741,0.0001759918,0.0001420095,0.0001287846,0.0002204323],"domain_scores_gemma":[0.9995373,0.00005093958,0.00001758338,0.0001901109,0.00005874582,0.0001452675],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003508834,0.000039676,0.002382857,0.00004338904,0.0002680427,0.00001159299,0.001788437,0.005205093,0.0006658501,0.001515036,0.9811332,0.006911777],"study_design_scores_gemma":[0.001958375,0.0003854239,0.0002351622,0.00003831499,0.0002417678,0.00000421498,0.003396697,0.7650682,0.003478111,0.001963118,0.222408,0.0008225749],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1716869,0.0006442304,0.657812,0.002194041,0.0006639686,0.0005953567,0.00008455979,0.0007883597,0.1655306],"genre_scores_gemma":[0.9762757,0.00001496456,0.004046777,0.0003252246,0.0002319456,0.00001298771,0.00001888801,0.00003186702,0.01904163],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8045888,"threshold_uncertainty_score":0.4660907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07755381976741021,"score_gpt":0.2576940652587252,"score_spread":0.180140245491315,"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."}}