{"id":"W7112437764","doi":"","title":"Scalable Urban Crowdsensing: Data Contributor and Consumer Dynamics","year":2025,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scalability; Key (lock); Routing (electronic design automation); Service (business); Data collection; Aggregate (composite); Resource allocation; Resource (disambiguation); Data aggregator; Aggregate data","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":[0.00355352,0.0008671953,0.001017173,0.0009630834,0.001160266,0.002200354,0.002119318,0.001381753,0.002058994],"category_scores_gemma":[0.01216612,0.0006047168,0.000640696,0.00170426,0.00128403,0.003323443,0.003827492,0.001394972,0.0004027387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001512046,"about_ca_system_score_gemma":0.001195048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009729349,"about_ca_topic_score_gemma":0.008398649,"domain_scores_codex":[0.9977587,0.0007845188,0.00007328244,0.000619752,0.0005028033,0.0002609411],"domain_scores_gemma":[0.9911145,0.005994003,0.000663707,0.0009507749,0.0009036514,0.000373442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001718443,0.0007304651,0.08743764,0.001010183,0.0004605402,0.001675857,0.00365611,0.5690885,0.01623857,0.08139993,0.02285412,0.2137297],"study_design_scores_gemma":[0.00003622731,0.00009241946,0.00859601,0.00005212192,0.00004483097,0.0001869296,0.001314164,0.9490023,0.001760749,0.03221966,0.006638267,0.00005624453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5298865,0.002967457,0.4345731,0.008603998,0.0005038642,0.0006389265,0.002792564,0.001376072,0.01865754],"genre_scores_gemma":[0.9821598,0.000466266,0.01499685,0.0001896162,0.00009155782,0.00009091169,0.0004382207,0.00007166628,0.001495149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009729349,"threshold_uncertainty_score":0.01934546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198468489645481,"score_gpt":0.1721620168894545,"score_spread":0.1601773319929997,"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."}}