{"id":"W6947739232","doi":"10.4121/16686154.v2","title":"Soil organic carbon stock and uncertainties, 30cm and 1m depth, at 250m spatial resolution in Canada, version 3.0","year":2021,"lang":"en","type":"dataset","venue":"4TU.ResearchData","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soil carbon; Permafrost; Soil water; Land cover; Stock (firearms); Spatial variability; Hydrology (agriculture); Quantile; Ground truth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004575595,0.0003540223,0.0003786633,0.00009272309,0.0002589761,0.0001046026,0.0006006564,0.0003262995,0.00080321],"category_scores_gemma":[0.0004427813,0.0003121682,0.00002451093,0.000446924,0.0003284541,0.0001385987,0.003661572,0.0009453354,0.00005557504],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004027121,"about_ca_system_score_gemma":0.0005848141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9822751,"about_ca_topic_score_gemma":0.9983926,"domain_scores_codex":[0.9962603,0.0003747107,0.0003049385,0.001025185,0.00130594,0.000728904],"domain_scores_gemma":[0.9983755,0.0001661302,0.0001172719,0.0009974836,0.00002524207,0.0003183913],"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":[0.00005311283,0.00002157016,0.003474521,0.00007646771,0.00001467897,0.00030118,0.00003396371,0.00009666738,0.001116824,8.387723e-8,0.9933473,0.001463611],"study_design_scores_gemma":[0.0007030278,0.0000843626,0.08396256,0.0002414501,0.00004270185,0.0001196486,0.0002667507,0.004325044,0.000315762,0.00001291156,0.9093132,0.000612586],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.3140502,0.000887094,0.00000155657,0.0007408728,0.00039418,0.0005836947,0.6829726,0.00001631308,0.0003535475],"genre_scores_gemma":[0.02147261,0.002545587,0.00007929425,0.0001233567,0.0001687995,0.000004157461,0.9745094,0.00003532467,0.001061515],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2925776,"threshold_uncertainty_score":0.9999331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352620630713846,"score_gpt":0.2233906860049172,"score_spread":0.2098644796977788,"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."}}