{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001536256,0.0001168757,0.0002030507,0.0001117847,0.00007889117,0.00009887326,0.0002220616,0.000165881,0.000001242259],"category_scores_gemma":[0.00007908534,0.0001040374,0.00006015148,0.0005057316,0.00005157059,0.0002769061,0.00001755343,0.0001702506,0.00002069375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005674498,"about_ca_system_score_gemma":0.00004832164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001848504,"about_ca_topic_score_gemma":0.000003032146,"domain_scores_codex":[0.9990665,0.0000124247,0.000450763,0.0000673481,0.0002317881,0.0001711471],"domain_scores_gemma":[0.9993919,0.00001102724,0.0001673027,0.0001286442,0.0002726357,0.00002855021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001658373,0.00003690484,0.003743319,0.000168255,0.0001260339,0.00006569776,0.0001091359,0.9284576,0.001996691,0.06089495,0.001572529,0.002812334],"study_design_scores_gemma":[0.03058017,0.006328314,0.07554667,0.02607269,0.001426515,0.04404634,0.07506852,0.08734088,0.4027692,0.2104534,0.03228324,0.008084039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3809786,0.008444978,0.6015892,0.0006224334,0.002829746,0.000242506,0.00001472733,0.001804306,0.003473565],"genre_scores_gemma":[0.9986392,0.00006597491,0.001161378,0.00001200061,0.00009928342,0.000003983646,0.000001994795,0.00001098021,0.000005232774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8411167,"threshold_uncertainty_score":0.4242523,"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."}}