{"id":"W4381122216","doi":"10.20944/preprints202306.1239.v1","title":"Resilient Localization and Coverage in the Internet of Things","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Winnipeg","funders":"","keywords":"Internet of Things; Computer science; Software deployment; Reliability (semiconductor); Context (archaeology); Network topology; Wireless sensor network; Computer security; Computer network; Geography","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":[0.0008691719,0.0005539002,0.000526943,0.0009424656,0.000667097,0.0008944733,0.0006723627,0.0009203329,0.0005809322],"category_scores_gemma":[0.004886041,0.0004076053,0.0005120116,0.0008922028,0.001267734,0.00188504,0.001812879,0.0006088841,0.0001691423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007875091,"about_ca_system_score_gemma":0.0003771515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001944921,"about_ca_topic_score_gemma":0.001393162,"domain_scores_codex":[0.9990707,0.0003211351,0.00003466347,0.0001955538,0.0002677543,0.0001101977],"domain_scores_gemma":[0.9985863,0.0007956816,0.0001953864,0.0002198685,0.000148577,0.00005432637],"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":[0.0001287082,0.00003880893,0.002750714,0.0001848679,0.00006605186,0.0005289112,0.0003216205,0.8156465,0.01251165,0.06859916,0.00259512,0.09662779],"study_design_scores_gemma":[0.000009477521,0.00008251015,0.001165226,0.00003123148,0.0000283374,0.0003585106,0.0001549472,0.9322346,0.003922577,0.05810423,0.003880334,0.00002798018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04289936,0.001852796,0.9493758,0.0008652225,0.0001233206,0.00004501724,0.00004847572,0.0006800672,0.004109927],"genre_scores_gemma":[0.9171214,0.001454438,0.07909296,0.0001527783,0.0001147688,0.00006745372,0.00007991694,0.00006449936,0.001851709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001944921,"threshold_uncertainty_score":0.00571382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0592521391433369,"score_gpt":0.2905908384793912,"score_spread":0.2313386993360543,"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."}}