{"id":"W6974364605","doi":"10.5880/isg.2004.001","title":"The Mexican gravimetric geoid: GGM04","year":2004,"lang":"en","type":"dataset","venue":"GFZ Data Services","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geoid; Geopotential; Terrain; Reference frame; Digital elevation model; Satellite; Computation; Undulation of the geoid; Gravity anomaly","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":[0.0004783428,0.001650261,0.001272143,0.00371596,0.0006790457,0.001487644,0.002695554,0.001075014,0.03002297],"category_scores_gemma":[0.00212231,0.0007350112,0.000843448,0.009383773,0.0002499031,0.001099745,0.00102384,0.001714037,0.03812504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257623,"about_ca_system_score_gemma":0.002129434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0934329,"about_ca_topic_score_gemma":0.06981894,"domain_scores_codex":[0.9995111,0.00004618076,0.00004508131,0.0001479519,0.0001427915,0.0001069453],"domain_scores_gemma":[0.9991014,0.00006182558,0.0001246579,0.0002462379,0.0003923522,0.00007359608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009058088,0.00003205892,0.003875079,0.0002831108,0.00003335763,0.00003137876,0.00004254998,0.001438793,0.0002503577,0.0009508774,0.9871832,0.005788514],"study_design_scores_gemma":[0.000143946,0.00001020475,0.01568089,0.0001351377,0.00002764951,0.00004268988,0.00009649763,0.001649865,0.0006487612,0.0005878242,0.980947,0.00002965729],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006387053,0.00002420319,0.0001456359,0.00003602318,0.00001499509,0.000009645081,0.9977921,0.0004748997,0.0008638328],"genre_scores_gemma":[0.0008758933,0.00002233288,0.0004026511,0.000007154374,0.000003838529,0.00005321227,0.9981072,0.00008997387,0.0004377688],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0934329,"threshold_uncertainty_score":0.1857781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03214074763435575,"score_gpt":0.3095146210858691,"score_spread":0.2773738734515133,"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."}}