{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001786459,0.000994775,0.0008085641,0.0007139067,0.000956102,0.001231779,0.0200292,0.0005639322,0.0006871097],"category_scores_gemma":[0.0001750625,0.0006915203,0.0001367453,0.00294578,0.0002817741,0.001043063,0.006983554,0.001298791,0.04453309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002635117,"about_ca_system_score_gemma":0.0005351684,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09391568,"about_ca_topic_score_gemma":0.155698,"domain_scores_codex":[0.9939098,0.0003111265,0.0008863722,0.00185199,0.001762475,0.001278269],"domain_scores_gemma":[0.9834349,0.0004780269,0.001069409,0.01448574,0.0001836417,0.000348243],"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":[0.00004482511,0.0001333808,0.0000141745,0.0005666514,0.000331161,0.00006433939,0.00001564075,0.000005624054,0.000003052154,0.0000264557,0.9978151,0.000979651],"study_design_scores_gemma":[0.0005087449,0.00005027073,0.0003364132,0.0002382191,0.0006636316,0.00003860155,0.0001625954,0.00002936584,0.000008190601,0.000408723,0.9967274,0.0008278628],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003339075,0.009080397,8.003915e-7,0.0002888876,0.001150956,0.0006728441,0.9883983,0.0002630884,0.0001113818],"genre_scores_gemma":[0.00001919299,0.003308698,0.0001228783,0.0007924687,0.0010382,0.00005712748,0.994383,0.0001955274,0.00008286825],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06178232,"threshold_uncertainty_score":0.999805,"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."}}