{"id":"W6955430331","doi":"10.5880/intermagnet.1991.2019","title":"Intermagnet Reference Data Set (IRDS) 2019 – Definitive Magnetic Observatory Data","year":2023,"lang":"en","type":"dataset","venue":"GFZ Data Services","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Data set; Observatory; Data archive; Data quality; Reference data; Set (abstract data type); Digital data","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":["metaepi_narrow","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.004337626,0.00234606,0.002195524,0.0009132972,0.0004742306,0.001717905,0.1104414,0.00136437,0.002792635],"category_scores_gemma":[0.001023115,0.002413452,0.00007989387,0.002104873,0.0005891809,0.01026716,0.1766703,0.003112772,0.2956318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001939367,"about_ca_system_score_gemma":0.001340232,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1223432,"about_ca_topic_score_gemma":0.3067226,"domain_scores_codex":[0.982555,0.001273849,0.002254162,0.00890503,0.0027727,0.002239309],"domain_scores_gemma":[0.9107202,0.001372838,0.001883597,0.0849029,0.0004193577,0.0007011257],"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":[0.00019909,0.0002491365,0.00008846435,0.003244373,0.000509731,0.0007254073,0.00005102748,0.000001201746,0.00001519867,0.000006650623,0.9940505,0.0008591926],"study_design_scores_gemma":[0.001094779,0.0001924581,0.002123375,0.001935188,0.002131999,0.00009497919,0.0006509003,0.002231084,0.000001343392,0.00006276745,0.9869936,0.002487542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001248495,0.007270207,0.000001327301,0.0002551139,0.002508917,0.001454448,0.9871526,0.001072847,0.0001596311],"genre_scores_gemma":[0.00000545669,0.008526943,0.0007783991,0.002071824,0.001233936,0.00008569795,0.9862558,0.0006759721,0.0003660004],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2928392,"threshold_uncertainty_score":0.9999321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2587288361838049,"score_gpt":0.3671322460283033,"score_spread":0.1084034098444984,"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."}}