{"id":"W2820073091","doi":"10.4095/308231","title":"Residual total magnetic field, aeromagnetic survey of the Marsh Lake area, Yukon, part of NTS 105-E/south","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":"Marsh; Geology; Aeromagnetic survey; Residual; Hydrology (agriculture); Physical geography; Geomorphology; Geography; Geotechnical engineering; Magnetic field; Ecology; Wetland; Mathematics","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":[0.00007911895,0.0002134461,0.0001546914,0.0008268129,0.0007061721,0.0002980079,0.000376389,0.0002237952,0.001995375],"category_scores_gemma":[0.0002478626,0.0001443574,0.0001309631,0.001127798,0.0001659514,0.000250478,0.0003951131,0.000207387,0.0005489921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001221448,"about_ca_system_score_gemma":0.004733973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7048356,"about_ca_topic_score_gemma":0.8281805,"domain_scores_codex":[0.999917,0.000005801848,0.000007762843,0.0000144948,0.00003246032,0.00002250588],"domain_scores_gemma":[0.999737,0.00001111185,0.00002532933,0.00001488508,0.0001653368,0.00004633724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002572961,0.00010563,0.9593508,0.0001463767,0.00009596983,0.0004993988,0.00130395,0.0006979873,0.0123548,0.0003400298,0.01054505,0.01430279],"study_design_scores_gemma":[0.00001589755,0.00002374091,0.9944174,0.000006665675,0.00001448613,0.00005247487,0.0008231635,0.0003180002,0.0005066502,0.00001348511,0.003804812,0.000003238445],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9756177,0.00005489623,0.0001693209,0.00007158521,0.000008120594,0.00004932664,0.01917225,0.00003403462,0.004822725],"genre_scores_gemma":[0.9686657,0.00008476598,0.0005439006,0.0000348845,0.000004294364,0.00005141512,0.02049373,0.00001190149,0.01010955],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2951644,"threshold_uncertainty_score":0.5938053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06264852511849646,"score_gpt":0.228817804889281,"score_spread":0.1661692797707845,"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."}}