{"id":"W2121862004","doi":"10.5081/jgps.3.1.2","title":"GNSS Indoor Location Technologies","year":2004,"lang":"en","type":"article","venue":"Journal of Global Positioning Systems","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GNSS applications; Computer science; Remote sensing; Environmental science; Geography; Global Positioning System; 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":[0.0002504522,0.0005984897,0.0004764632,0.000988481,0.0005296761,0.001230027,0.0005774543,0.0008398036,0.008668959],"category_scores_gemma":[0.0005463166,0.0002492235,0.0002679696,0.001280995,0.0003620882,0.0008984674,0.0009290676,0.000724283,0.01061837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004388171,"about_ca_system_score_gemma":0.0005423762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002199396,"about_ca_topic_score_gemma":0.00369175,"domain_scores_codex":[0.9995443,0.0000906682,0.00001860141,0.00006668007,0.0002283639,0.0000512613],"domain_scores_gemma":[0.9995618,0.00004099674,0.00003305503,0.0001143248,0.0002249149,0.00002485435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001896678,0.00005952055,0.004460486,0.000267637,0.00005962031,0.0003014514,0.0002250238,0.01669799,0.05427726,0.04454263,0.04095289,0.837966],"study_design_scores_gemma":[0.00003554434,0.0003027511,0.01120431,0.0002527,0.0001641439,0.002043006,0.0003330634,0.04841136,0.06010142,0.02039766,0.8566577,0.00009642881],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.03275527,0.007854777,0.7398622,0.00189911,0.00192946,0.0000792691,0.001143299,0.006506768,0.2079698],"genre_scores_gemma":[0.5314913,0.01146975,0.1677164,0.00114411,0.001428589,0.0001576989,0.005830638,0.0006165917,0.280145],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.008668959,"threshold_uncertainty_score":0.02900058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004626310086811352,"score_gpt":0.2075545377484016,"score_spread":0.2029282276615902,"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."}}