{"id":"W4390467500","doi":"10.47112/neufmbd.2023.15","title":"Hassas Nokta Konumlama (PPP) Yöntemindeki Hata Kaynaklarının Konum Belirleme Performansı Üzerindeki Etkilerinin İncelenmesi: PPPH Yazılımı Örneği","year":2023,"lang":"tr","type":"article","venue":"Necmettin Erbakan Üniversitesi Fen ve Mühendislik Bilimleri Dergisi","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; Necmettin Erbakan Üniversitesi","keywords":"Physics; Gynecology; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.001557878,0.002750332,0.002332822,0.002212348,0.001872852,0.001237812,0.003580237,0.001769992,0.004974311],"category_scores_gemma":[0.0003536393,0.003259403,0.001419255,0.003793917,0.0007914453,0.003077185,0.001918199,0.003330711,0.01392352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160905,"about_ca_system_score_gemma":0.0005142594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004682331,"about_ca_topic_score_gemma":0.0001588638,"domain_scores_codex":[0.9872122,0.0004426048,0.002376834,0.003336447,0.00226139,0.004370496],"domain_scores_gemma":[0.9930741,0.0009035541,0.0008490467,0.003021569,0.000629412,0.001522359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001487872,0.001922244,0.02968032,0.004059596,0.005409445,0.003010073,0.02652095,0.02069958,0.0395738,0.01270868,0.8153923,0.0395351],"study_design_scores_gemma":[0.01456721,0.004271155,0.1285133,0.006264399,0.003252617,0.0008667694,0.02591869,0.2223858,0.04079971,0.001528224,0.5374156,0.01421655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8982069,0.004831062,0.00120243,0.00328468,0.008440431,0.002343613,0.002002453,0.004875482,0.07481292],"genre_scores_gemma":[0.9654247,0.00272089,0.002059634,0.0005586785,0.001784546,0.0001550436,0.001620634,0.0006744019,0.02500149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2779768,"threshold_uncertainty_score":0.999799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796758275450279,"score_gpt":0.2213988518211309,"score_spread":0.2034312690666281,"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."}}