{"id":"W4411933070","doi":"10.1016/j.asr.2025.06.076","title":"A comprehensive study of geomagnetic and TEC disturbances in relation to M  <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si9.svg\"> <mml:mrow> <mml:mo>⩾</mml:mo> </mml:mrow> </mml:math>  5.0 earthquakes","year":2025,"lang":"lv","type":"article","venue":"Advances in Space Research","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Commission Géologique du Canada; National Institute of Information and Communications Technology; Universiti Kebangsaan Malaysia; Kyushu University; U.S. Geological Survey; Universitetet i Tromsø; Ministry of Higher Education, Malaysia; Florida Institute of Technology","keywords":"TEC; Relation (database); Earth's magnetic field; Computer science; Physics; Data mining; Geophysics; Ionosphere","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002552149,0.0001521778,0.000251267,0.001010232,0.0002032333,0.0004033346,0.0001250621,0.000211401,0.0003805257],"category_scores_gemma":[0.0006191591,0.0001210562,0.0001910078,0.001674583,0.0001509472,0.0003393728,0.0004261699,0.0001763987,0.00009674135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002222809,"about_ca_system_score_gemma":0.0003560776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006302936,"about_ca_topic_score_gemma":0.01577675,"domain_scores_codex":[0.9998441,0.00002109707,0.00002297674,0.00003804147,0.0000419327,0.00003174491],"domain_scores_gemma":[0.9993827,0.00009029582,0.0002883982,0.00003798586,0.0001074257,0.00009304172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009798825,0.00004673601,0.9765624,0.00009288645,0.0001112443,0.0004767705,0.0006568214,0.0006952566,0.004500439,0.0001139372,0.0003214698,0.01632404],"study_design_scores_gemma":[3.948122e-7,0.00001436181,0.9993311,0.000002816707,0.000007782377,0.00005333268,0.0001226569,0.0001484317,0.00007622262,0.000007764807,0.0002334575,0.000001693674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983276,0.0003205815,0.0002241193,0.00001559972,0.000002177424,0.000009195317,0.0005831414,0.000005635068,0.0005120562],"genre_scores_gemma":[0.998268,0.0003458053,0.0002237542,0.000009844415,0.00001028886,0.000007224163,0.0008916304,0.000002090212,0.0002412802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006302936,"threshold_uncertainty_score":0.01253247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02344292284718763,"score_gpt":0.2921973168852036,"score_spread":0.268754394038016,"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."}}