{"id":"W6947967946","doi":"10.4121/16686154","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":"4TU.ResearchData","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Permafrost; Soil carbon; Soil water; Land cover; Stock (firearms); Spatial variability; Hydrology (agriculture); Digital soil mapping","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":[0.0006739865,0.001183489,0.0007425836,0.003016416,0.001120104,0.001872339,0.001660304,0.000570188,0.005104519],"category_scores_gemma":[0.001639511,0.0006874939,0.001282877,0.006834495,0.0003574696,0.0008201747,0.0008659287,0.0007586744,0.002474456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00856239,"about_ca_system_score_gemma":0.01468994,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9791734,"about_ca_topic_score_gemma":0.9855549,"domain_scores_codex":[0.9995024,0.00002351062,0.00002439357,0.000112403,0.0002318248,0.0001053669],"domain_scores_gemma":[0.9985361,0.00005120974,0.00006637262,0.00009005787,0.00114845,0.0001078037],"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":[0.0009874624,0.0002676059,0.2895741,0.002379355,0.001454785,0.0008439353,0.001381937,0.06232703,0.01086239,0.004370359,0.444958,0.180593],"study_design_scores_gemma":[0.0002539074,0.00003985531,0.6153063,0.0005810197,0.0002615452,0.0002717653,0.001026659,0.07394198,0.006780059,0.001316996,0.2999534,0.0002664794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1006106,0.001391346,0.006838017,0.0002469659,0.0000655503,0.0001428252,0.8790352,0.005635541,0.006034005],"genre_scores_gemma":[0.1460726,0.0008953444,0.02246384,0.0001048733,0.0000163076,0.0002051383,0.8249854,0.0006057004,0.004650774],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02082658,"threshold_uncertainty_score":0.06212473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191999921271184,"score_gpt":0.2626321928691009,"score_spread":0.2507121936563891,"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."}}