{"id":"W2754432013","doi":"10.1145/3130906","title":"Rapid","year":2017,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Identification (biology); Noise (video); Fuse (electrical); Key (lock); Channel (broadcasting); Real-time computing; Gait; Artificial intelligence; Telecommunications; Engineering; Computer security; Electrical engineering","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":[0.00009768832,0.0001965588,0.0002455632,0.0001457942,0.0003762632,0.0001405303,0.002232631,0.0001938717,0.000009773634],"category_scores_gemma":[0.001492839,0.0001353149,0.00007309979,0.0001070838,0.0004875529,0.0003655119,0.001181962,0.0003773536,0.000008173746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004377875,"about_ca_system_score_gemma":0.000005464869,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009780794,"about_ca_topic_score_gemma":0.000001751106,"domain_scores_codex":[0.9991975,0.000001813446,0.0001954094,0.000219248,0.0001417523,0.0002442551],"domain_scores_gemma":[0.9988135,0.00005830356,0.0001740037,0.0008156382,0.0001244238,0.00001409697],"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":[0.0001897217,0.0001654148,0.01464194,0.0006338208,0.0003327368,0.000003675845,0.001026968,0.0002850301,0.2443702,0.01879769,0.02044766,0.6991051],"study_design_scores_gemma":[0.0001889933,0.0001983411,0.001772109,0.0002528986,0.00001576623,0.000008927143,0.003090637,0.0003424179,0.9674021,0.02056194,0.005990418,0.0001754721],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782402,0.0008599939,0.00001105438,0.0008275851,0.0003547263,0.0003634619,0.000007995243,0.001486659,0.01784832],"genre_scores_gemma":[0.9976303,0.001691145,0.0002995144,0.00001714257,0.00001977443,0.0001377023,1.638765e-7,0.00002433568,0.0001799506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7230319,"threshold_uncertainty_score":0.5517983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113285649075886,"score_gpt":0.2364010572457525,"score_spread":0.2250724923381639,"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."}}