{"id":"W3035272030","doi":"10.1139/cjss-2020-0025","title":"Comparisons of the prediction results of soil properties based on fuzzy <i>c</i>-means clustering and expert knowledge from laboratory Visible – Near-Infrared reflectance spectroscopy data","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Soil Science","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Partial least squares regression; Soil organic matter; Cluster analysis; Silt; Multivariate statistics; Artificial neural network; Organic matter; Soil fertility; Soil test; Soil science; Environmental science; Mathematics; Artificial intelligence; Computer science; Chemistry; Statistics; Soil water; Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.002700774,0.0005642029,0.0004529467,0.001405854,0.0002884703,0.0006560717,0.0005165262,0.000799842,0.0007408303],"category_scores_gemma":[0.007067703,0.0001711684,0.0007740238,0.000513198,0.0002805264,0.0008893539,0.0002130947,0.0003764089,0.0002712203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005442335,"about_ca_system_score_gemma":0.000451498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01199945,"about_ca_topic_score_gemma":0.009003641,"domain_scores_codex":[0.9990844,0.0002849263,0.00007654708,0.0002048487,0.0002627761,0.00008656459],"domain_scores_gemma":[0.9964907,0.00194496,0.0002112127,0.000240161,0.00102851,0.00008447182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002094185,0.0005708514,0.08450489,0.000391197,0.0005817145,0.0001994846,0.0007382084,0.5553399,0.04302155,0.001420663,0.002581946,0.3085555],"study_design_scores_gemma":[0.00002316144,0.0001913443,0.03689636,0.00001808902,0.00008039439,0.00004436337,0.0002045253,0.9446884,0.01702964,0.0004286382,0.0003288988,0.00006621171],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9357049,0.0002361361,0.06109343,0.00007472449,0.00003352817,0.00003677702,0.0001742468,0.0004652877,0.002180781],"genre_scores_gemma":[0.9850007,0.00008361344,0.01404298,0.00002081188,0.000008435764,0.00002417024,0.0002773986,0.00002325917,0.0005186377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01199945,"threshold_uncertainty_score":0.0238592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03671216470789242,"score_gpt":0.2489944408277223,"score_spread":0.2122822761198299,"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."}}