{"id":"W2057935927","doi":"10.1145/2702123.2702296","title":"Mobile Gamification for Crowdsourcing Data Collection","year":2015,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Crowdsourcing; Computer science; Task (project management); Data collection; Android (operating system); Human–computer interaction; Crowdsourcing software development; Data science; Multimedia; World Wide Web; Software; Engineering; Software development","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01245582,0.001490958,0.001034367,0.00243669,0.001273833,0.002449186,0.003196456,0.001725492,0.009618555],"category_scores_gemma":[0.03339492,0.0007486998,0.001201004,0.001681445,0.001329842,0.002212558,0.005752973,0.001371866,0.00272355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001343164,"about_ca_system_score_gemma":0.001817196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003033336,"about_ca_topic_score_gemma":0.005141848,"domain_scores_codex":[0.9913102,0.005601313,0.0003287757,0.0009972278,0.001358651,0.0004038701],"domain_scores_gemma":[0.9845363,0.009365719,0.0006652394,0.003092632,0.001441311,0.0008988346],"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":[0.00491645,0.002274184,0.01847677,0.002430917,0.0005630473,0.001588771,0.005141631,0.04694255,0.02571584,0.1010398,0.03639651,0.7545135],"study_design_scores_gemma":[0.001241392,0.001852273,0.02047815,0.001204978,0.0002273689,0.00104445,0.002529704,0.5465396,0.01664397,0.2585543,0.1491783,0.0005053809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04655542,0.0006872293,0.916798,0.002214398,0.0004147949,0.006054459,0.0009913841,0.00720758,0.0190767],"genre_scores_gemma":[0.3006523,0.000300839,0.6872034,0.000455799,0.0001106835,0.00593217,0.0007021513,0.0003169912,0.004325719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01245582,"threshold_uncertainty_score":0.06587344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029384342985967,"score_gpt":0.3123220569854691,"score_spread":0.2093836226868724,"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."}}