{"id":"W3178743083","doi":"10.3390/ijgi10070471","title":"Panoramic Street-Level Imagery in Data-Driven Urban Research: A Comprehensive Global Review of Applications, Techniques, and Practical Considerations","year":2021,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Panorama; Pedestrian; Computer science; Scale (ratio); Data science; Geography; Cartography; Transport engineering; Artificial intelligence; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001018077,0.00008777108,0.0001934611,0.0001210215,0.000070382,0.00006554275,0.0002007803,0.00005722285,0.0003932277],"category_scores_gemma":[0.0004808769,0.00008240129,0.00003670185,0.0001951268,0.0001735902,0.002795519,0.0003415417,0.0002848881,0.00004281335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004567239,"about_ca_system_score_gemma":0.0002459559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038497,"about_ca_topic_score_gemma":0.00006750764,"domain_scores_codex":[0.9978265,0.000158661,0.0008242213,0.0001024487,0.0009204494,0.0001677015],"domain_scores_gemma":[0.9986342,0.0002044558,0.0005345807,0.0002328294,0.0002927365,0.0001012345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005096174,0.002048833,0.486804,0.002322927,0.0004507514,0.0007337433,0.002240925,0.0002708867,0.002181901,0.03726582,0.2988853,0.1662853],"study_design_scores_gemma":[0.002152622,0.0002634634,0.4017221,0.002571875,0.00008043982,0.003077827,0.00181761,0.0009582373,0.001213633,0.004617794,0.5811141,0.0004102659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5878814,0.02135727,0.07208832,0.2375437,0.001880978,0.007533235,0.005691959,0.0001472137,0.0658759],"genre_scores_gemma":[0.9150429,0.02301661,0.05703818,0.004052713,0.000173178,0.00002287791,0.0006171757,0.000008482331,0.0000278877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3271615,"threshold_uncertainty_score":0.4305568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1103037261864708,"score_gpt":0.4161843416295197,"score_spread":0.3058806154430488,"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."}}