{"id":"W3198896842","doi":"10.1007/s11265-022-01752-9","title":"Online Dynamic Window (ODW) Assisted Two-Stage LSTM Frameworks For Indoor Localization","year":2022,"lang":"en","type":"article","venue":"Journal of Signal Processing Systems","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Inertial measurement unit; Context (archaeology); Artificial intelligence; Window (computing); Heading (navigation); Field (mathematics); Sliding window protocol; Real-time computing; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005887242,0.0002158202,0.0004322993,0.0004163337,0.0003621153,0.0001602586,0.0003816973,0.0002078191,0.00003443137],"category_scores_gemma":[0.00007301839,0.0002016154,0.0001358525,0.000607008,0.00004719351,0.0003109041,0.00004435819,0.0008589866,0.000001166041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004080247,"about_ca_system_score_gemma":0.0001332115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005390967,"about_ca_topic_score_gemma":0.000003292891,"domain_scores_codex":[0.9980345,0.00006845497,0.0009111698,0.0001533166,0.0005307362,0.0003018033],"domain_scores_gemma":[0.9987544,0.00009214329,0.0005649341,0.0001309386,0.0003871173,0.00007045867],"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":[0.0000673071,0.0001003264,0.0003507525,0.0006469,0.00007967205,0.00002665897,0.0002973299,0.9752418,0.004861511,0.0002157331,0.0005322709,0.01757968],"study_design_scores_gemma":[0.001252314,0.0002343432,0.00009444437,0.000370066,0.00006314639,0.0001979763,0.002977462,0.9826193,0.001165609,0.000210587,0.01053774,0.0002770042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02624486,0.003794077,0.9680879,0.00008946511,0.0009761683,0.0003383885,0.00007174628,0.0002611184,0.0001363508],"genre_scores_gemma":[0.9977782,0.00002534331,0.001489838,0.00008169487,0.0002485357,0.00003673657,0.00004395294,0.00007239843,0.0002232928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9715334,"threshold_uncertainty_score":0.8221638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358725443114948,"score_gpt":0.2600478559222237,"score_spread":0.2464606014910743,"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."}}