{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03414785,0.001860296,0.001823696,0.004343196,0.001081103,0.003541511,0.00318916,0.002491285,0.005912122],"category_scores_gemma":[0.03240187,0.0006348774,0.002214252,0.003193586,0.001187808,0.002646841,0.003793005,0.002131947,0.007422904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002037732,"about_ca_system_score_gemma":0.007060803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01978268,"about_ca_topic_score_gemma":0.00511644,"domain_scores_codex":[0.9891726,0.003428644,0.000509133,0.0008642629,0.005187959,0.0008373816],"domain_scores_gemma":[0.9554132,0.00597177,0.002260985,0.01355358,0.02072197,0.002078459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001297797,0.0008447816,0.03257972,0.001311566,0.0005443096,0.0004305922,0.001181069,0.1033209,0.05922713,0.01280325,0.1964004,0.5900585],"study_design_scores_gemma":[0.0004005889,0.001457576,0.04750536,0.00146162,0.0003674314,0.0005494455,0.0008389608,0.1595442,0.09907766,0.01438499,0.6740723,0.0003397643],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1465476,0.00634571,0.5936468,0.01170842,0.004848427,0.006476492,0.06403266,0.03323828,0.1331556],"genre_scores_gemma":[0.3051306,0.004013633,0.4396506,0.001785383,0.001384346,0.003469961,0.1762848,0.01827154,0.05000907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03414785,"threshold_uncertainty_score":0.1805932,"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."}}