{"id":"W2912199117","doi":"10.1109/access.2019.2899169","title":"A Novel Outlier Immune Multipath Fingerprinting Model for Indoor Single-Site Localization","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Jiangxi Provincial Department of Science and Technology; National Natural Science Foundation of China","keywords":"Computer science; Outlier; Pattern recognition (psychology); Multipath propagation; Artificial intelligence; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008113497,0.000850255,0.001134273,0.000805304,0.0004246876,0.0008763415,0.00243346,0.001288257,0.001643638],"category_scores_gemma":[0.002034131,0.0003731546,0.0009233556,0.001358216,0.0007271909,0.001484927,0.001005476,0.00129155,0.000596049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008113176,"about_ca_system_score_gemma":0.0009885668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009520467,"about_ca_topic_score_gemma":0.005907374,"domain_scores_codex":[0.9994037,0.00009974867,0.00002968771,0.0001679972,0.0001874527,0.0001115078],"domain_scores_gemma":[0.999302,0.0002154477,0.0001285619,0.00006975066,0.0002470627,0.00003714073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001148738,0.00004105285,0.001765978,0.00008138851,0.00005303693,0.0001632584,0.0000897986,0.9177238,0.004060345,0.01163016,0.001234928,0.06304131],"study_design_scores_gemma":[0.000003061262,0.00001899183,0.0001352163,0.000002668632,0.00000679901,0.00002699318,0.000005123712,0.9979133,0.0002916601,0.001294117,0.0002957621,0.000006241211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01106507,0.0002141459,0.9871839,0.0001118504,0.00004034329,0.00001947508,0.00009046509,0.0003213591,0.0009533473],"genre_scores_gemma":[0.8600691,0.000826951,0.1298805,0.0001826737,0.0001127946,0.0001819377,0.0005709791,0.0001166216,0.008058519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009520467,"threshold_uncertainty_score":0.01893014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02996522448085833,"score_gpt":0.2552164267166676,"score_spread":0.2252512022358092,"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."}}