{"id":"W4224924188","doi":"10.1139/cjss-2022-0040","title":"Comparing direct and indirect approaches to predicting soil texture class","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Ministry of Agriculture, Food and Rural Affairs","funders":"","keywords":"Soil texture; Silt; Texture (cosmology); Soil science; Soil water; Soil map; Class (philosophy); Environmental science; Mathematics; Geology; Computer science; Artificial intelligence; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01401496,0.001935124,0.0009362868,0.00254574,0.0008195876,0.002870946,0.001723262,0.0008996162,0.001543608],"category_scores_gemma":[0.0329486,0.0005330564,0.001706656,0.001592755,0.0007719138,0.001875713,0.0033997,0.001586181,0.0006983791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001963764,"about_ca_system_score_gemma":0.002213557,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05074068,"about_ca_topic_score_gemma":0.07699955,"domain_scores_codex":[0.9918223,0.00449426,0.0003300778,0.001491447,0.001512028,0.0003499357],"domain_scores_gemma":[0.9711873,0.02056534,0.001154423,0.001981988,0.004551971,0.0005589896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001218853,0.0004869583,0.6285625,0.0004718202,0.003061388,0.0001894385,0.001508509,0.1782674,0.00301952,0.002485447,0.002205016,0.1785232],"study_design_scores_gemma":[0.0001034967,0.0007276906,0.1916989,0.000203029,0.0007883519,0.0001914057,0.001225373,0.792113,0.004602536,0.004219106,0.003890531,0.0002366046],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9036174,0.0009082571,0.08024933,0.0004392937,0.000101384,0.0003429849,0.00159367,0.000761955,0.01198583],"genre_scores_gemma":[0.9418089,0.00030364,0.05290096,0.0001245492,0.00003685834,0.0002166944,0.002119128,0.0001675339,0.002321743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9492593,"threshold_uncertainty_score":0.1008907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04726578902208186,"score_gpt":0.205529711386603,"score_spread":0.1582639223645211,"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."}}