{"id":"W7123284940","doi":"10.5683/sp3/7vguge","title":"Replication Data for: Drivers of soil C quality and stability: Insights from a topsoil dataset at landscape scale in Ontario, Canada","year":2025,"lang":"","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture, Food and Rural Affairs; University of Guelph","funders":"","keywords":"Topsoil; Soil quality; Agriculture; Scale (ratio); Soil classification; Soil test; Subsoil; Soil fertility; Soil water; Soil functions","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":[0.001786969,0.0009049523,0.0008463918,0.002444461,0.002898939,0.001938637,0.002243018,0.0007238893,0.01016529],"category_scores_gemma":[0.007567336,0.0005069002,0.0008800811,0.007293961,0.0008353271,0.0005543642,0.001592247,0.000775904,0.004538012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01629246,"about_ca_system_score_gemma":0.03532022,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.988041,"about_ca_topic_score_gemma":0.9939041,"domain_scores_codex":[0.9985887,0.0001145324,0.0001001465,0.0003363928,0.0005574072,0.0003028434],"domain_scores_gemma":[0.9912942,0.0005661223,0.000825318,0.001081857,0.005298056,0.0009344065],"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":[0.000553391,0.00009454587,0.2016866,0.001414658,0.0005512963,0.0002799503,0.00116771,0.002026119,0.001358189,0.001405412,0.7709637,0.01849843],"study_design_scores_gemma":[0.0004237469,0.00003509377,0.5981426,0.0003509516,0.0001795757,0.0001023989,0.0009288904,0.001620334,0.0007121456,0.0004462828,0.3969465,0.0001114197],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01269325,0.0002801086,0.0003253357,0.0002153786,0.00002701972,0.00009502454,0.9837495,0.0002244588,0.002390021],"genre_scores_gemma":[0.03743399,0.0002219082,0.001733072,0.0001177267,0.00001874947,0.0003092349,0.9559493,0.0000972959,0.004118658],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01629246,"threshold_uncertainty_score":0.1182106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05233979329062142,"score_gpt":0.2997644090641537,"score_spread":0.2474246157735323,"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."}}