{"id":"W6898791217","doi":"10.57757/iugg23-4537","title":"Activities of the JWG 4.3.4 - Validation of VTEC models for high-precision and high resolution applications","year":2023,"lang":"en","type":"article","venue":"Publication Database GFZ (GFZ German Research Centre for Geosciences)","topic":"GNSS positioning and interference","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"VTEC; GNSS applications; Consistency (knowledge bases); Satellite; High resolution; Ionosphere; Calibration; Nowcasting","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":[0.001588844,0.00009937126,0.000131506,0.0004176974,0.0003902386,0.00009892257,0.000506151,0.00005903563,0.00001517086],"category_scores_gemma":[0.0004223925,0.00008349677,0.00004457926,0.00120341,0.0002915287,0.0008712413,0.0001733938,0.0001226401,0.000004194051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006845812,"about_ca_system_score_gemma":0.00008728323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002849052,"about_ca_topic_score_gemma":0.00004834389,"domain_scores_codex":[0.9983441,0.00008243657,0.0003310054,0.0003121653,0.0005697801,0.0003605557],"domain_scores_gemma":[0.9980776,0.0005241517,0.0001118581,0.0005484978,0.0006582199,0.00007968028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001869204,0.0004664229,0.0005588905,0.002119191,0.0000905508,1.095593e-7,0.002961963,0.0368266,0.1319135,0.5726443,0.19771,0.05452157],"study_design_scores_gemma":[0.0006670774,0.0001041653,0.00634011,0.0002060737,0.00002621587,0.00000149112,0.0005764384,0.7530227,0.1914167,0.03207881,0.01531912,0.0002411336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6540603,0.0001243639,0.3265188,0.00356927,0.0003735968,0.003550527,0.01090134,0.000288352,0.000613394],"genre_scores_gemma":[0.9944587,0.0001016557,0.002296495,0.000007659811,0.00005010906,0.0006534145,0.001925737,0.00001466819,0.0004915568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7161961,"threshold_uncertainty_score":0.34049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05573759111705855,"score_gpt":0.3321427485837935,"score_spread":0.2764051574667349,"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."}}