{"id":"W2520036727","doi":"10.1145/2968219.2968590","title":"MobiBee","year":2016,"lang":"en","type":"article","venue":"","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Fingerprint (computing); Code (set theory); Vulnerability (computing); Fingerprint recognition; Computer security; Real-time computing; Data mining","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":[0.0006561055,0.001012643,0.0005409486,0.001067488,0.0008278401,0.001660443,0.001436811,0.0009932707,0.06736264],"category_scores_gemma":[0.002130269,0.0004012761,0.0005123597,0.0005152836,0.0003264906,0.002239375,0.003998268,0.0008063287,0.05130251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002911337,"about_ca_system_score_gemma":0.0005438562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001510671,"about_ca_topic_score_gemma":0.00253236,"domain_scores_codex":[0.9994549,0.000094027,0.0000265313,0.0001097672,0.0002113147,0.0001033729],"domain_scores_gemma":[0.999117,0.0001306882,0.00005843379,0.0002951031,0.0001960673,0.0002027087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00201921,0.0003752548,0.004763213,0.001310479,0.0001169681,0.0008887283,0.001285248,0.001916953,0.04544142,0.0386753,0.2861408,0.6170664],"study_design_scores_gemma":[0.00009026702,0.0001999463,0.003450561,0.0001271751,0.00002511358,0.0006217398,0.0002624667,0.008950206,0.008560439,0.005660808,0.9719918,0.00005962304],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.04049134,0.003276088,0.2956875,0.002128813,0.002467002,0.002373764,0.02042652,0.07661951,0.5565294],"genre_scores_gemma":[0.2582886,0.002311086,0.2102273,0.001578886,0.0005083787,0.002029913,0.03065812,0.007655684,0.4867419],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06736264,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007045602901884863,"score_gpt":0.193736832040626,"score_spread":0.1866912291387412,"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."}}