{"id":"W4389274253","doi":"10.3389/fsoil.2023.1305105","title":"Improving a regional peat thickness map using soil apparent electrical conductivity measurements at the field-scale","year":2023,"lang":"en","type":"article","venue":"Frontiers in Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Dalhousie University; Université Laval; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","funders":"","keywords":"Peat; Kriging; Soil science; Digital soil mapping; Linear regression; Covariate; Regression analysis; Scale (ratio); Mean squared error; Digital elevation model; Environmental science; Hydrology (agriculture); Mathematics; Soil map; Soil water; Statistics; Geology; Remote sensing; Geography; Cartography; Geotechnical 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":[0.0004148611,0.0005310012,0.0002621426,0.0008979889,0.0002248323,0.0006229562,0.0004277607,0.0002034033,0.001062332],"category_scores_gemma":[0.0008166144,0.0001277498,0.0003356663,0.0007615646,0.0001235387,0.000373762,0.0002418892,0.000185301,0.0003974635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008651373,"about_ca_system_score_gemma":0.001191182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1531598,"about_ca_topic_score_gemma":0.2418388,"domain_scores_codex":[0.9998631,0.0000205855,0.000006333657,0.00005625066,0.00002961706,0.00002416094],"domain_scores_gemma":[0.9995998,0.00007634716,0.00005869711,0.00004050388,0.0002044466,0.0000202366],"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":[0.0003841215,0.0002058591,0.303791,0.0003404229,0.0001586576,0.0002566681,0.000289311,0.2659424,0.06973036,0.0003329787,0.001744255,0.356824],"study_design_scores_gemma":[0.00003014885,0.00007747182,0.2773212,0.00006212611,0.00007297347,0.00008298231,0.0002986632,0.704323,0.01524341,0.0002259028,0.00221643,0.0000456041],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351834,0.000291135,0.05704113,0.00006888511,0.00001326799,0.00007729427,0.002593618,0.00202892,0.002702332],"genre_scores_gemma":[0.9534575,0.00009460482,0.04480047,0.000008735829,0.000003672617,0.00002829883,0.0009544945,0.0000401193,0.0006122196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1531598,"threshold_uncertainty_score":0.3045366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03729985262424907,"score_gpt":0.2694314956409971,"score_spread":0.232131643016748,"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."}}