{"id":"W2888301647","doi":"10.1145/3229434.3229447","title":"Mobiceil","year":2018,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Ceiling (cloud); Computer science; Phone; Computer vision; Mobile phone; Table (database); Camera phone; Artificial intelligence; Real-time computing; Computer graphics (images); Telecommunications; Engineering; Data mining","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":[0.00001220315,0.00002855589,0.00002470631,0.00002535218,0.00001757133,0.000006658253,0.00004972998,0.00002883095,0.0005017099],"category_scores_gemma":[0.000005341982,0.00002401646,0.00000764942,0.0000767018,0.00002812175,0.00002858308,0.000007199292,0.00001942034,0.0006468558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006302363,"about_ca_system_score_gemma":0.000001145879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000165494,"about_ca_topic_score_gemma":0.000005328322,"domain_scores_codex":[0.9998409,7.165669e-7,0.00003628409,0.0000295505,0.00002528926,0.0000672689],"domain_scores_gemma":[0.9998972,0.000002750396,0.000001528426,0.00007588758,0.00001425869,0.000008403569],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005382018,0.00002520994,0.003415725,0.00005474209,0.00006374775,0.000006554236,0.0008045416,0.00257799,0.02917918,0.2888067,0.46456,0.2105002],"study_design_scores_gemma":[0.000139728,0.00003395525,0.0007349158,0.000003412632,0.000002541603,0.000003112703,0.0001631435,0.05472005,0.6903916,0.002866579,0.250781,0.0001600138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06933732,0.00005039128,0.2087,0.00005556715,0.000430308,0.00004077536,6.766214e-7,0.00411086,0.7172741],"genre_scores_gemma":[0.9979224,0.000007039165,0.00113679,0.00006221304,0.00005386547,0.000001970707,4.829316e-7,0.000005865759,0.0008093676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9285851,"threshold_uncertainty_score":0.8314239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00425894005148099,"score_gpt":0.1833745842301475,"score_spread":0.1791156441786665,"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."}}