{"id":"W3195994334","doi":"10.3390/app11167669","title":"Sampling Rate Impact on Precise Point Positioning with a Low-Cost GNSS Receiver","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"GNSS positioning and interference","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"GNSS applications; Precise Point Positioning; Geodetic datum; Computer science; Sampling (signal processing); Geodesy; Remote sensing; Real-time computing; Global Positioning System; Telecommunications; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001971471,0.0007166748,0.0004433881,0.0008251592,0.0003527285,0.0009166739,0.000572692,0.0007726486,0.002708562],"category_scores_gemma":[0.008214843,0.0002442044,0.0003780804,0.001413104,0.0003733718,0.0008531282,0.0006127823,0.0006806143,0.001193071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004036976,"about_ca_system_score_gemma":0.0005860148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00370293,"about_ca_topic_score_gemma":0.003013832,"domain_scores_codex":[0.9980018,0.0004174997,0.00009819641,0.0002691032,0.001057228,0.0001562656],"domain_scores_gemma":[0.9974281,0.001130371,0.0001690209,0.0003844714,0.0008430849,0.0000448342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002359235,0.0001879645,0.03564397,0.001356999,0.0001672442,0.0007070034,0.001068683,0.1492669,0.3333361,0.006097587,0.003374598,0.4664337],"study_design_scores_gemma":[0.0002468904,0.001957128,0.1132097,0.0002884305,0.0005182432,0.001923186,0.0009781549,0.3550256,0.4849246,0.004160559,0.03649515,0.0002723198],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4677969,0.001443062,0.5121818,0.0004146139,0.0003702639,0.0001594256,0.0006969316,0.00262417,0.01431276],"genre_scores_gemma":[0.8539193,0.0006393305,0.1414279,0.0001000076,0.00005671644,0.00007523839,0.0008370639,0.0004002637,0.002544236],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00370293,"threshold_uncertainty_score":0.01042622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0166343943825385,"score_gpt":0.2555229689071097,"score_spread":0.2388885745245712,"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."}}