{"id":"W6894294765","doi":"10.5683/sp3/d8kcyz","title":"Soil organic carbon stock and uncertainties, 30cm and 1m depth, at 250m spatial resolution in Canada, version 3.0","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service; World Wildlife Fund Canada; University of Toronto; McMaster University","funders":"","keywords":"Permafrost; Soil carbon; Soil water; Land cover; Stock (firearms); Ground truth; Digital soil mapping; Spatial variability; Hydrology (agriculture)","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":[0.0006886678,0.001191069,0.0007471222,0.003053083,0.001127115,0.001896192,0.001677165,0.0005739877,0.004776689],"category_scores_gemma":[0.001704161,0.000690761,0.001297358,0.007013877,0.0003550984,0.00083154,0.0008490996,0.0007605804,0.002307278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009069266,"about_ca_system_score_gemma":0.01532727,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9804732,"about_ca_topic_score_gemma":0.9863508,"domain_scores_codex":[0.999495,0.00002300244,0.00002485658,0.0001128813,0.0002400594,0.0001040752],"domain_scores_gemma":[0.9984388,0.00005543539,0.00007094346,0.00009767395,0.00122572,0.0001114493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009861762,0.0002721664,0.3105987,0.002406374,0.001550605,0.0008472258,0.001396838,0.06884223,0.01094002,0.004521549,0.4142213,0.1834168],"study_design_scores_gemma":[0.0002491403,0.00003947272,0.6269957,0.0005860265,0.0002657558,0.0002614331,0.0009990371,0.07480027,0.006839329,0.001341838,0.2873559,0.0002660479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1060033,0.001376165,0.006730688,0.0002467511,0.00006442082,0.000140735,0.8736594,0.005623679,0.006154815],"genre_scores_gemma":[0.152643,0.0008968602,0.02207779,0.0001051429,0.00001562361,0.0001984585,0.8189017,0.0006220361,0.004539493],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01952684,"threshold_uncertainty_score":0.0658024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01100188173493532,"score_gpt":0.2140988379249566,"score_spread":0.2030969561900213,"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."}}