{"id":"W2799820718","doi":"10.1016/j.scs.2018.04.028","title":"Spatio-temporal promenades as representations of urban atmospheres","year":2018,"lang":"en","type":"article","venue":"Sustainable Cities and Society","topic":"Urban Heat Island Mitigation","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Microclimate; Atmosphere (unit); Pedestrian; Urban environment; Perception; Temporality; Architectural engineering; Representation (politics); Space (punctuation); Built environment; Urban design; Urban planning; Field (mathematics); Environmental psychology; Geography; Computer science; Civil engineering; Meteorology; Engineering; Environmental planning; Psychology; Mathematics; Social psychology; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001336518,0.00007495889,0.00009125918,0.00000419325,0.0002772315,0.00003214557,0.00006564581,0.0000487609,0.001629203],"category_scores_gemma":[0.00003179956,0.00006816583,0.00004761177,0.0001442988,0.0006222588,0.0002588998,0.0001052119,0.00004505648,0.00001392075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008882995,"about_ca_system_score_gemma":0.00003195449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004086567,"about_ca_topic_score_gemma":0.00009334096,"domain_scores_codex":[0.9993048,0.00002256446,0.0001335171,0.0001671694,0.0001551661,0.0002167664],"domain_scores_gemma":[0.9996918,0.00002815652,0.00005460369,0.0001319382,0.00004205129,0.00005146115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002001409,0.00004845643,0.7294312,0.0001289908,0.00003413565,0.000003509074,0.0450799,0.00002821785,0.0002818785,0.01686905,0.2074389,0.0006358296],"study_design_scores_gemma":[0.001090906,0.000766244,0.4122253,0.00003704321,0.00005856916,0.00001196675,0.3430384,0.001756371,0.007137076,0.06082074,0.1725478,0.000509597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9665684,0.00006960276,0.00012031,0.0001988449,0.0000303281,0.0002173778,0.000004291694,0.00002507973,0.03276583],"genre_scores_gemma":[0.955648,0.00002777974,0.001398889,0.0001032967,0.00007125994,0.00002098605,0.00001249445,0.000007634102,0.04270967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3172058,"threshold_uncertainty_score":0.9992834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006108457759364491,"score_gpt":0.2256303596001379,"score_spread":0.2195219018407734,"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."}}