{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001656727,0.0001105312,0.000129533,0.00001366717,0.00009456566,0.0001158626,0.0002861487,0.00004803806,0.005770492],"category_scores_gemma":[0.00003162678,0.00009653023,0.00001585007,0.00006979026,0.00009380253,0.0002049378,0.00043581,0.00006425631,0.001216513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002290701,"about_ca_system_score_gemma":0.00001102425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005565661,"about_ca_topic_score_gemma":0.0003769264,"domain_scores_codex":[0.9991943,0.00001629516,0.0001161807,0.0003519107,0.0001088868,0.0002124072],"domain_scores_gemma":[0.9995236,0.00006250874,0.00006339529,0.0002541947,0.000005378608,0.00009088673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001644838,0.0001202493,0.03621383,0.00002659376,0.00005444893,0.00002610647,0.001484418,0.0003233957,0.006392958,0.00009082178,0.23974,0.7153627],"study_design_scores_gemma":[0.001236215,0.00008123298,0.02890337,0.00002662683,0.00002589125,0.00001356762,0.0001233435,0.005502853,0.001133561,0.0005756654,0.962119,0.0002586547],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9752964,0.00003206836,0.0002641942,0.0003062577,0.000165555,0.0008932243,0.01255559,0.000001809164,0.01048488],"genre_scores_gemma":[0.9602997,0.00003964965,0.0257833,0.0008370531,0.00006372676,0.00003394501,0.006695108,0.0000329897,0.006214579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.722379,"threshold_uncertainty_score":0.9995611,"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."}}