{"id":"W2138381158","doi":"10.1190/geo2012-0225.1","title":"Mitigating remanent magnetization effects in magnetic data using the normalized source strength","year":2013,"lang":"en","type":"article","venue":"Geophysics","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"Commonwealth Scientific and Industrial Research Organisation","keywords":"Remanence; Magnetization; Stoner–Wohlfarth model; Magnetic anomaly; Geology; Rock magnetism; Magnetic field; Natural remanent magnetization; Potential field; Field (mathematics); Geophysics; Mineralogy; Mathematics; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002214437,0.0001531851,0.0001844218,0.00003453057,0.0001570957,0.0001068281,0.000475045,0.0000490944,0.0003800537],"category_scores_gemma":[0.0001478232,0.0001022463,0.00003658956,0.0006159561,0.00006714675,0.0003012706,0.00007050289,0.0002260776,0.0002809816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003842492,"about_ca_system_score_gemma":0.00002448341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01015512,"about_ca_topic_score_gemma":0.0002804227,"domain_scores_codex":[0.9985008,0.0002943015,0.0002202145,0.0003161224,0.0002637588,0.0004047703],"domain_scores_gemma":[0.9987485,0.0005799027,0.00008054948,0.0004701001,0.00003408864,0.00008684555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001013615,0.00003973808,0.01470049,0.0000454051,0.000005842948,0.000003406984,0.0001857809,0.005991005,0.0007273868,0.00007855573,0.0001085337,0.9781037],"study_design_scores_gemma":[0.0002150972,0.00009849455,0.4253185,0.00001886808,0.00001710137,0.000002010638,0.00005026252,0.5657039,0.0001329033,0.008015499,0.0002857613,0.0001415684],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959662,0.0003083321,0.002372468,0.0002081616,0.0001340638,0.0003940916,0.00001094707,0.00003263071,0.0005730937],"genre_scores_gemma":[0.9913958,0.00001079465,0.007695889,0.0003146741,0.0002255638,0.000003476866,0.000154189,0.000005525806,0.0001941292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9779621,"threshold_uncertainty_score":0.9964364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851302237884141,"score_gpt":0.2363204075934295,"score_spread":0.2178073852145881,"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."}}