{"id":"W111456786","doi":"","title":"Assisting personal positioning in indoor environments using map matching","year":2011,"lang":"en","type":"article","venue":"Archives of Photogrammetry Cartography and Remote Sensing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Inertial measurement unit; Map matching; Computer science; Global Positioning System; Geospatial analysis; GNSS applications; Inertial navigation system; Real-time computing; Mobile mapping; USable; Computer vision; Matching (statistics); Position (finance); Artificial intelligence; Orientation (vector space); Remote sensing; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004126034,0.0006422927,0.0007580713,0.001376122,0.0003767156,0.000797675,0.0008389693,0.0005431051,0.002588806],"category_scores_gemma":[0.001105469,0.0002634565,0.0004193468,0.001826647,0.0001911728,0.00118698,0.001255351,0.0003404837,0.001936765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000201184,"about_ca_system_score_gemma":0.0003956877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001856348,"about_ca_topic_score_gemma":0.001564282,"domain_scores_codex":[0.9995359,0.00008032536,0.00002128662,0.0001064665,0.0002031155,0.00005288368],"domain_scores_gemma":[0.9996945,0.00006381924,0.0000279808,0.00008251486,0.0001102455,0.00002095533],"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":[0.0002601643,0.00009941037,0.002687895,0.0001870567,0.00007771234,0.0003340188,0.000266073,0.0436165,0.03608034,0.004140898,0.004026183,0.9082236],"study_design_scores_gemma":[0.00005150685,0.0002679677,0.006743995,0.00004832197,0.0001052153,0.0009906461,0.0004020057,0.8816648,0.06859912,0.008429213,0.03261235,0.00008496434],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02389672,0.0001860996,0.9680297,0.00004047944,0.0000601989,0.00006294932,0.0001545959,0.003705557,0.003863629],"genre_scores_gemma":[0.4466058,0.000423279,0.5467477,0.00004876481,0.00004711438,0.00009920715,0.0005434635,0.0001959755,0.005288758],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002588806,"threshold_uncertainty_score":0.008660436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01333861016533478,"score_gpt":0.2001454026104215,"score_spread":0.1868067924450868,"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."}}