{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006738687,0.001167704,0.0007238645,0.00300817,0.001099996,0.00184715,0.001660991,0.0005695161,0.004827146],"category_scores_gemma":[0.001670882,0.0006809715,0.001272119,0.006927788,0.0003500953,0.0008200641,0.0008356972,0.0007337557,0.002319451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008939809,"about_ca_system_score_gemma":0.01468159,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9806538,"about_ca_topic_score_gemma":0.9865234,"domain_scores_codex":[0.9995155,0.00002284406,0.00002442471,0.0001100892,0.0002261435,0.0001010106],"domain_scores_gemma":[0.9984989,0.00005462229,0.00007103981,0.00009413598,0.001170755,0.0001105326],"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":[0.001006494,0.0002774232,0.3190051,0.002386964,0.001543566,0.0008581631,0.001412465,0.0685607,0.01068577,0.004431544,0.4084548,0.1813771],"study_design_scores_gemma":[0.0002484298,0.00003938489,0.6393782,0.0005707591,0.0002564764,0.0002534045,0.0009972716,0.07269858,0.006488211,0.001263606,0.2775493,0.0002564478],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1082447,0.001357855,0.006684733,0.0002470935,0.00006282849,0.0001414728,0.8713678,0.005615517,0.006278055],"genre_scores_gemma":[0.1575174,0.0008830586,0.02199149,0.0001061108,0.0000155224,0.0002003649,0.8140811,0.000595531,0.004609326],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01934618,"threshold_uncertainty_score":0.06486309,"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."}}