{"id":"W3092248123","doi":"10.20383/101.0154","title":"Aggregated gridded soil texture dataset for Mackenzie and Nelson-Churchill River Basins.","year":2019,"lang":"en","type":"article","venue":"Open MIND","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Soil texture; Hydrology (agriculture); Drainage basin; Geology; Environmental science; Physical geography; Soil water; Soil science; Cartography; Geography","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":[0.0005776362,0.0007583502,0.0007251501,0.002075744,0.0005472542,0.0009216882,0.001856516,0.000620456,0.01020086],"category_scores_gemma":[0.002322987,0.0003467377,0.0006502799,0.003488041,0.0002506753,0.0004608018,0.001096391,0.0008178124,0.007210081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002881067,"about_ca_system_score_gemma":0.004825328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5840828,"about_ca_topic_score_gemma":0.7599381,"domain_scores_codex":[0.9994175,0.00005489406,0.00005806856,0.0001419913,0.0002313056,0.00009625997],"domain_scores_gemma":[0.9982159,0.0001193221,0.000152649,0.0002687949,0.001051439,0.0001919262],"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":[0.000104707,0.00005289987,0.01722043,0.0004472339,0.0001278159,0.00008414703,0.00008735558,0.001565359,0.0006960614,0.001054279,0.9676099,0.01094986],"study_design_scores_gemma":[0.0001813206,0.00002184658,0.1240594,0.0002488975,0.00006816482,0.00008410211,0.0002995822,0.006715115,0.001431821,0.001164668,0.8656345,0.00009055744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002398654,0.00005837732,0.000253456,0.0000616096,0.00001621168,0.000025256,0.9960405,0.0002865975,0.0008592752],"genre_scores_gemma":[0.003762417,0.00003385302,0.0009601284,0.00003099795,0.000003647336,0.00006672991,0.9944531,0.0000436694,0.0006454514],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4159172,"threshold_uncertainty_score":0.8367332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02109575384616047,"score_gpt":0.2672504604332244,"score_spread":0.246154706587064,"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."}}