{"id":"W4402978230","doi":"10.1109/tmc.2024.3470993","title":"Long-Term or Temporary? Hybrid Worker Recruitment for Mobile Crowd Sensing and Computing","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Aeronautical Science Foundation of China; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Computer science; Term (time); Mobile computing; Crowd sourcing; Mobile telephony; Computer security; Computer network; World Wide Web; Mobile radio","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0008971867,0.0005142115,0.0005063143,0.000407397,0.001122843,0.001281758,0.0004213202,0.0001374105,0.00001396764],"category_scores_gemma":[0.00001081529,0.0004703874,0.0002815782,0.0006845954,0.0001264087,0.0004129573,0.0000317459,0.0005775178,0.00002698682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000195672,"about_ca_system_score_gemma":0.000175253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002944562,"about_ca_topic_score_gemma":0.00001399097,"domain_scores_codex":[0.9966018,0.0001571669,0.0007299048,0.001334811,0.0003667407,0.0008096244],"domain_scores_gemma":[0.9973761,0.001348372,0.0001467041,0.0007438337,0.0001306829,0.0002543512],"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":[0.00003769211,0.0001075475,0.00003997649,0.0002684775,0.0001102248,0.0001817476,0.001244255,0.07849614,0.001395299,0.00003430714,0.0002359012,0.9178484],"study_design_scores_gemma":[0.000666213,0.0005634695,0.00006802223,0.001640672,0.00007245783,0.0007696402,0.0002070851,0.9717882,0.02121504,0.00007265338,0.002250445,0.0006860555],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2723039,0.0007846444,0.7221575,0.00007414207,0.002166205,0.001449817,0.00001026351,0.0009963467,0.0000571587],"genre_scores_gemma":[0.9638738,0.00004736469,0.03494672,0.0001951498,0.0003324696,0.00008498819,0.000005468147,0.00008858534,0.0004254456],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9171624,"threshold_uncertainty_score":0.9997748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04354741402426556,"score_gpt":0.3081453854050173,"score_spread":0.2645979713807518,"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."}}