{"id":"W3023316863","doi":"10.1051/e3sconf/202016404015","title":"Accessibility of the urban environment for people with limited mobility using the example of Arkhangelsk","year":2020,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recreation; Quarter (Canadian coin); Quality (philosophy); Environmental planning; Stairs; Space (punctuation); Transport engineering; Business; Relevance (law); Urban planning; Geography; Built environment; Computer science; Civil engineering; Engineering; Political science","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":[0.0008180511,0.0001146936,0.0003405464,0.00001537687,0.0002053639,0.00002282688,0.0008792076,0.00006711114,0.0003370608],"category_scores_gemma":[0.0001534932,0.00006105886,0.000139361,0.0002967495,0.001197762,0.00016531,0.00006403311,0.0000901129,1.688288e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002015033,"about_ca_system_score_gemma":0.0008315687,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008174548,"about_ca_topic_score_gemma":0.006223494,"domain_scores_codex":[0.9984549,0.0001833839,0.0004202397,0.0002893532,0.0004668533,0.0001852568],"domain_scores_gemma":[0.9986071,0.000309696,0.0004643032,0.0004013018,0.000155792,0.00006183105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001214568,0.0001290147,0.9880909,0.00009183997,0.00003403576,3.585013e-8,0.008467337,0.00002352444,0.001444996,0.001021512,0.00002775718,0.0005475766],"study_design_scores_gemma":[0.00042604,0.0001443386,0.9703501,0.00004396657,0.0001163018,2.428681e-8,0.006497561,0.0005406656,0.0135506,0.0008708858,0.007332559,0.0001269325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952139,0.0001297726,0.0006000519,0.001099459,0.00008738828,0.0007848592,0.00008272409,0.0000120201,0.001989807],"genre_scores_gemma":[0.999526,0.00002050171,0.0003002847,0.0000383949,0.00006354354,0.0000179768,0.000003876815,0.000004806075,0.00002461438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01774079,"threshold_uncertainty_score":0.9984301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07949261227015274,"score_gpt":0.2900127269567203,"score_spread":0.2105201146865676,"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."}}