{"id":"W7115894507","doi":"10.3727/152599525x17640248309319","title":"Mobile Based Measurement of Event Experiences","year":2025,"lang":"en","type":"article","venue":"Event Management","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Systems, Applications & Products in Data Processing (Canada); Toronto Metropolitan University","funders":"","keywords":"Event (particle physics); Mobile phone; Event management; Phone; Demographics; Set (abstract data type); Event monitoring; Data collection; Check-in","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001100058,0.0002525484,0.0002615918,0.002917612,0.0005492517,0.002087411,0.0005326379,0.0004582164,0.006656441],"category_scores_gemma":[0.01112503,0.0001677121,0.0002971653,0.002231153,0.0003309074,0.001367952,0.00171323,0.0005001327,0.001262611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005133557,"about_ca_system_score_gemma":0.0003010239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002535685,"about_ca_topic_score_gemma":0.004173025,"domain_scores_codex":[0.9986361,0.0005688014,0.0001422512,0.0002152779,0.0003204039,0.0001172093],"domain_scores_gemma":[0.994512,0.002133068,0.001349132,0.000372186,0.00113101,0.000502656],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004411071,0.0004238067,0.8003482,0.0009751574,0.0002451991,0.0004841409,0.03494209,0.001657543,0.003860823,0.006154656,0.005098843,0.1453685],"study_design_scores_gemma":[0.00002136091,0.000531076,0.9320475,0.0002512823,0.00008023493,0.0005436363,0.03988892,0.002691658,0.00165406,0.001900214,0.0203054,0.0000846902],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.940595,0.0003934705,0.008866675,0.0002547706,0.00007039571,0.0004990966,0.006849822,0.0001496507,0.04232116],"genre_scores_gemma":[0.9903511,0.0002959378,0.004775928,0.00004357355,0.00003541461,0.0003876429,0.001863073,0.00001840007,0.002228876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006656441,"threshold_uncertainty_score":0.022268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687439987636493,"score_gpt":0.3159142594436698,"score_spread":0.2990398595673049,"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."}}