{"id":"W4255808759","doi":"10.4095/308229","title":"Residual total magnetic field, aeromagnetic survey of the Marsh Lake area, Yukon, part of NTS 105-D/north","year":2018,"lang":"en","type":"report","venue":"","topic":"Geological Studies and Exploration","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Aeromagnetic survey; Marsh; Geology; Residual; Archaeology; Field survey; Physical geography; Geochemistry; Geography; Seismology; Wetland; Magnetic field; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009249501,0.0002259373,0.0001634112,0.0008436622,0.0006428573,0.0003020937,0.0003891898,0.0002217367,0.001809539],"category_scores_gemma":[0.0002655137,0.0001451334,0.000140519,0.001152224,0.0001589052,0.000257389,0.0003705277,0.000206305,0.0005396398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001335978,"about_ca_system_score_gemma":0.004998102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7205717,"about_ca_topic_score_gemma":0.8349115,"domain_scores_codex":[0.9999071,0.000006845914,0.000008664534,0.00001662841,0.00003711268,0.00002357876],"domain_scores_gemma":[0.9996969,0.00001201318,0.00002857802,0.00001753079,0.0001936981,0.00005142995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003238015,0.0001267025,0.9537665,0.0001702482,0.0001200075,0.0004696106,0.001124852,0.0009818935,0.01244448,0.0003614331,0.01448335,0.01562712],"study_design_scores_gemma":[0.00001911052,0.00002688413,0.9934983,0.00000718319,0.00001676563,0.00004586353,0.0006608642,0.000381866,0.0006460379,0.00001417166,0.004679374,0.000003513222],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615958,0.00006919221,0.000250849,0.00008645076,0.00001169944,0.00006309726,0.03174618,0.00005089366,0.006125845],"genre_scores_gemma":[0.957582,0.000095817,0.0007220776,0.00004167731,0.000005250997,0.0000612871,0.03033032,0.00001577138,0.0111457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2794283,"threshold_uncertainty_score":0.5621478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0586585531410508,"score_gpt":0.2271609677051678,"score_spread":0.168502414564117,"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."}}