{"id":"W2079895116","doi":"10.1190/1.2370388","title":"Evaluating normalized magnetic derivatives for structural mapping","year":2006,"lang":"en","type":"article","venue":"","topic":"Geophysical and Geoelectrical Methods","field":"Earth and Planetary Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geology; Lineament; Magnetic anomaly; Basement; Tectonics; Fault (geology); Seismology; Geophysics","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":[0.001895281,0.0009888083,0.0005883168,0.002595048,0.0004143514,0.001799023,0.0008739404,0.0006376247,0.008212551],"category_scores_gemma":[0.01013359,0.0003187283,0.0006185288,0.001431148,0.0004103368,0.001479409,0.0009481311,0.0005565597,0.001888024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001045339,"about_ca_system_score_gemma":0.00134704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01094865,"about_ca_topic_score_gemma":0.01066165,"domain_scores_codex":[0.9989416,0.0002437703,0.00006458353,0.0001541895,0.0005145786,0.0000813159],"domain_scores_gemma":[0.9971766,0.0008737608,0.0001877935,0.0003561035,0.001302485,0.0001031856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004544201,0.0001288914,0.01281246,0.000201991,0.0001179298,0.0001726473,0.0001592666,0.2448654,0.02080735,0.007130705,0.005477076,0.7076719],"study_design_scores_gemma":[0.00001494478,0.0000647557,0.00625518,0.00002726844,0.00002334952,0.00008723586,0.00009552155,0.9746318,0.01128864,0.004108262,0.003380561,0.00002249137],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1488514,0.0006517626,0.8290514,0.000295446,0.000156308,0.00018574,0.001286669,0.005552087,0.01396925],"genre_scores_gemma":[0.6429358,0.0003688294,0.3469554,0.00005420984,0.00004817097,0.0000989067,0.002667141,0.000896039,0.005975349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01094865,"threshold_uncertainty_score":0.02747369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04571398880325805,"score_gpt":0.3082637637783079,"score_spread":0.2625497749750499,"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."}}