{"id":"W7128870755","doi":"","title":"Developing and testing a mobile application to observe activities in public spaces: Results of a case study in Montreal, Canada","year":2022,"lang":"","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Mobile device; Data collection; Quality (philosophy); Key (lock)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001729545,0.001078375,0.0003923964,0.001016142,0.002449638,0.001647942,0.001795602,0.0009042412,0.002056768],"category_scores_gemma":[0.003428075,0.0004397807,0.0004562657,0.001382859,0.001273532,0.000811371,0.001185373,0.0005977486,0.0007383842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009859492,"about_ca_system_score_gemma":0.01624671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9340627,"about_ca_topic_score_gemma":0.9747638,"domain_scores_codex":[0.9987085,0.0003075027,0.00005743331,0.0002584466,0.0003648764,0.0003032395],"domain_scores_gemma":[0.9977291,0.0005515195,0.00008407346,0.000111134,0.001138306,0.0003858076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001291863,0.006556259,0.2319065,0.001592688,0.0003285455,0.008571231,0.09554675,0.02342579,0.1061295,0.003357863,0.01647467,0.5048183],"study_design_scores_gemma":[0.0005704153,0.004391835,0.6421336,0.0006622539,0.0005533518,0.001160281,0.101455,0.07670877,0.05913763,0.0007754855,0.1119871,0.0004643298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762914,0.0002574403,0.01113819,0.0004157994,0.00002683165,0.001510392,0.001151367,0.0005191781,0.008689386],"genre_scores_gemma":[0.9405167,0.0004915525,0.04177096,0.0001534216,0.00001103731,0.0005535703,0.001528231,0.0001255402,0.01484904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06593728,"threshold_uncertainty_score":0.1326512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04148120888099614,"score_gpt":0.2610496500817852,"score_spread":0.219568441200789,"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."}}