{"id":"W4408325107","doi":"10.1109/globecom52923.2024.10901333","title":"An Efficient Online Task Assignment Algorithm for Hybrid Mobile Crowdsensing","year":2024,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Crowdsensing; Computer science; Task (project management); Algorithm; Computer security; 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":[0.0005610797,0.0002529187,0.0002291779,0.0001777234,0.0002684822,0.0009963344,0.0004724189,0.0000582367,0.00001558413],"category_scores_gemma":[0.00001470685,0.0002166499,0.0001596116,0.0003143923,0.00005337642,0.0002674196,0.0001335225,0.0001690323,0.0000441959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001258215,"about_ca_system_score_gemma":0.000123125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003033657,"about_ca_topic_score_gemma":0.000003499038,"domain_scores_codex":[0.9978217,0.0000600247,0.0003445855,0.0008731207,0.0003542781,0.0005462978],"domain_scores_gemma":[0.9986418,0.0002018374,0.00004398614,0.0007920468,0.0001055003,0.0002148132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001985818,0.0002163993,0.000001419872,0.00003531518,0.00002866641,0.00008877681,0.0004494604,0.0288132,0.0107466,0.00262386,0.002410741,0.9545836],"study_design_scores_gemma":[0.0001869344,0.0002475788,0.000008396958,0.00008232553,0.00001590022,0.000122226,0.0001309362,0.9564195,0.01990934,0.0003445244,0.02223167,0.0003006264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03633752,0.0004483885,0.95961,0.0002508225,0.001398597,0.0004667185,0.00003083546,0.001123986,0.0003331312],"genre_scores_gemma":[0.6943457,0.000004775263,0.3043083,0.0003063827,0.000356522,0.00003521346,0.00002700299,0.00003356677,0.0005826067],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9542829,"threshold_uncertainty_score":0.9607675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100119627078188,"score_gpt":0.2721227308539957,"score_spread":0.2611215345832139,"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."}}