{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009581675,0.0000421845,0.00004183082,0.00003013816,0.00004189213,0.00005001228,0.0002637128,0.00001696441,0.00005234052],"category_scores_gemma":[0.00001766325,0.00002242521,0.00002353523,0.00009216559,0.00001630221,0.0001783487,0.00008104094,0.00001558771,0.0004556782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009876505,"about_ca_system_score_gemma":0.00001234473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005106197,"about_ca_topic_score_gemma":0.00000141328,"domain_scores_codex":[0.9995578,0.00001199962,0.0000612667,0.0001529068,0.00008059527,0.0001354451],"domain_scores_gemma":[0.9995211,0.00004966673,0.00001280633,0.000349386,0.00002099661,0.00004609035],"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":[6.061829e-7,0.00001201062,0.0004758299,0.000001262115,0.000003600569,0.000009099565,0.00008297087,0.000002419362,0.04096521,0.2479245,0.01023595,0.7002865],"study_design_scores_gemma":[0.001682174,0.0002101162,0.01033068,0.0001544908,0.000006283833,0.0002374963,0.00005143739,0.01331164,0.4796411,0.06198754,0.4313124,0.001074668],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02378176,0.00001359833,0.9327909,0.002051851,0.0001602154,0.00002087779,7.620761e-8,0.0002991924,0.04088146],"genre_scores_gemma":[0.9718369,0.000002338827,0.0195826,0.0003293469,0.00003608149,0.000001625607,1.660355e-8,0.000002660282,0.008208388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9480552,"threshold_uncertainty_score":0.5856974,"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."}}