{"id":"W2498633402","doi":"","title":"Positioning accuracy and availability analysis of three commercial WADGPS services","year":2000,"lang":"en","type":"article","venue":"GEOMATICA","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Forestry; Humanities; Cartography; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0006020488,0.0003093793,0.0003508419,0.00106348,0.0004013561,0.0005786,0.000517898,0.0004777357,0.002455814],"category_scores_gemma":[0.004399597,0.0001721572,0.0002061053,0.002181453,0.0002476545,0.0004796967,0.0003272103,0.0001912988,0.0005311162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104056,"about_ca_system_score_gemma":0.0004498134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06031301,"about_ca_topic_score_gemma":0.05262616,"domain_scores_codex":[0.9993088,0.00008747602,0.00005313973,0.0001417524,0.0003176293,0.00009118736],"domain_scores_gemma":[0.9968994,0.001226717,0.0002553225,0.0001851003,0.001356149,0.00007733096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00306263,0.0002210079,0.4054514,0.0007199076,0.0003263931,0.001046228,0.001616001,0.2730234,0.05752343,0.001885772,0.003736185,0.2513877],"study_design_scores_gemma":[0.0000719502,0.0007715792,0.4854893,0.00003297165,0.0001742692,0.0006025051,0.001568631,0.4727469,0.03232993,0.0004131768,0.005729454,0.00006924948],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992784,0.0001732309,0.004193397,0.00004382488,0.000007452301,0.00001534102,0.0007274845,0.0002715203,0.001783751],"genre_scores_gemma":[0.9967046,0.0000600083,0.001721534,0.000005941474,0.000003456125,0.000008408134,0.0008531222,0.00002029131,0.0006225916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06031301,"threshold_uncertainty_score":0.1199239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151705705104038,"score_gpt":0.27334885849039,"score_spread":0.2618318014393496,"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."}}