{"id":"W2059861708","doi":"10.1007/pl00012800","title":"Heading and Pitch Determination Using GPS/GLONASS","year":2000,"lang":"en","type":"article","venue":"GPS Solutions","topic":"GNSS positioning and interference","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"GLONASS; Global Positioning System; Real Time Kinematic; Heading (navigation); Computer science; GNSS applications; GPS disciplined oscillator; GPS signals; Precise Point Positioning; Assisted GPS; Geodesy; Telecommunications; Geography","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":[0.00004388632,0.00006594395,0.00005912184,0.00004656085,0.0001921298,0.00004177912,0.00003781771,0.00004082723,0.0001141663],"category_scores_gemma":[0.00000602153,0.00007631028,0.00001849163,0.00008241185,0.0000266507,0.0001539967,0.000008106382,0.00007959247,0.00005203357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005887227,"about_ca_system_score_gemma":0.000006444175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004503203,"about_ca_topic_score_gemma":0.00001561123,"domain_scores_codex":[0.9995916,0.00001003421,0.00009368073,0.00008661069,0.00004831052,0.0001697149],"domain_scores_gemma":[0.9998408,0.00001538611,0.000007115302,0.00007921474,0.00001606333,0.00004143183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002105673,0.0002263852,0.004555908,0.000282499,0.0001547336,0.00002252606,0.007418449,0.3369674,0.2333805,0.01597052,0.009635929,0.3913641],"study_design_scores_gemma":[0.0001453404,0.00002158938,0.006978841,0.0001035566,0.00002106344,0.00007338374,0.00004901757,0.9878357,0.001666042,0.0007089599,0.002209455,0.0001870178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9467636,0.0003158335,0.03048308,0.00005610556,0.0001493154,0.00005248178,0.000009055117,0.0002357327,0.02193478],"genre_scores_gemma":[0.9975489,0.00004333843,0.00203104,0.00001762802,0.00004932333,0.000005852067,0.000005697017,0.00001037136,0.0002878908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6508684,"threshold_uncertainty_score":0.3111843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856312274434143,"score_gpt":0.2450656755972046,"score_spread":0.2165025528528632,"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."}}