{"id":"W4256382289","doi":"10.21203/rs.3.rs-150227/v1","title":"Listening to Bluetooth Beacons for Epidemic Risk Mitigation","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institute for Advanced Research","keywords":"Beacon; Active listening; Bluetooth; Business; Computer science; Psychology; Telecommunications; Wireless; Communication","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":[0.0010372,0.0005516091,0.0006227517,0.001012112,0.0005391296,0.00124377,0.0009878752,0.0009718715,0.002720261],"category_scores_gemma":[0.006139718,0.0003422835,0.0003213207,0.0005509043,0.000425911,0.001239482,0.001624076,0.0007336404,0.0009446011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003001839,"about_ca_system_score_gemma":0.0003929681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001136884,"about_ca_topic_score_gemma":0.001051436,"domain_scores_codex":[0.9991574,0.0003176278,0.00003893586,0.0001494364,0.0002459407,0.00009058437],"domain_scores_gemma":[0.9967216,0.001831694,0.000362873,0.0005323378,0.0003899056,0.0001615523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001954269,0.0007370338,0.04099493,0.0009388108,0.0002657589,0.001053848,0.00234958,0.07359372,0.1151043,0.01733121,0.0237024,0.7219742],"study_design_scores_gemma":[0.0002125978,0.001248495,0.0146221,0.0002089399,0.0003306986,0.001268392,0.0008440706,0.8636,0.05869427,0.01882179,0.03998072,0.0001678479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2962327,0.003067797,0.6660529,0.002244515,0.0006960665,0.0003655745,0.0004697334,0.009923126,0.02094768],"genre_scores_gemma":[0.9513226,0.0005295081,0.04350354,0.0003795891,0.0001225122,0.000080353,0.000162394,0.0001002838,0.003799276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002720261,"threshold_uncertainty_score":0.009100199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.095293664527262,"score_gpt":0.4335921058243479,"score_spread":0.3382984412970859,"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."}}