{"id":"W4392616132","doi":"10.5194/egusphere-egu24-2176","title":"Predicting Soil Bulk Density in Boreal Podzolic Soil using Ground-Penetrating Radar and Electromagnetic Induction","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Ground-penetrating radar; Boreal; Environmental science; Radar; Bulk density; Electromagnetic induction; Soil science; Remote sensing; Geology; Soil water; Engineering; Aerospace engineering; Electrical engineering","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":[0.0002614268,0.000392731,0.0002719756,0.0005956193,0.0002777372,0.0006322002,0.0005337562,0.0003210935,0.0002097157],"category_scores_gemma":[0.0005158802,0.0002079785,0.0002318791,0.0005755098,0.0003181069,0.0003178668,0.0002311893,0.0002286302,0.00009135217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001866174,"about_ca_system_score_gemma":0.0007865101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3641237,"about_ca_topic_score_gemma":0.5493602,"domain_scores_codex":[0.9998435,0.00001236989,0.00001085181,0.0000593054,0.00003629379,0.00003759402],"domain_scores_gemma":[0.9996419,0.00009257279,0.00009475328,0.00001865555,0.0001080563,0.00004399911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004482952,0.0002492311,0.8989649,0.00009576714,0.00006009942,0.0004732208,0.0002719797,0.01792438,0.05761535,0.00006389867,0.000210534,0.0236224],"study_design_scores_gemma":[0.00002064632,0.0001055626,0.9761303,0.000008311463,0.00001800964,0.00008660884,0.0002534362,0.02088041,0.002309418,0.0000168432,0.0001579996,0.00001235354],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991415,0.00004033063,0.0003649025,0.000007118853,0.000001114668,0.0000114043,0.0001733677,0.00002084542,0.000239485],"genre_scores_gemma":[0.9981866,0.00007089267,0.001212949,0.000007609675,9.603502e-7,0.000007188347,0.0003579945,0.000002544273,0.0001531777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3641237,"threshold_uncertainty_score":0.7240086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01845043926670007,"score_gpt":0.2600249955786792,"score_spread":0.2415745563119791,"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."}}