{"id":"W3003029456","doi":"10.1016/j.compag.2020.105217","title":"Model prediction of depth-specific soil texture distributions with artificial neural network: A case study in Yunfu, a typical area of Udults Zone, South China","year":2020,"lang":"en","type":"article","venue":"Computers and Electronics in Agriculture","topic":"Soil and Unsaturated Flow","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Soil texture; Mean squared error; Texture (cosmology); Soil science; Artificial neural network; Silviculture; Soil water; Environmental science; Geology; Mathematics; Statistics; Image (mathematics); Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004519158,0.000169502,0.0002642186,0.00003428301,0.00004027617,0.00001908958,0.00007707354,0.0001245179,5.208975e-7],"category_scores_gemma":[0.000002741725,0.0001178619,0.00003575264,0.000559554,0.00002593518,0.00006069482,0.00002568282,0.0005231139,8.835291e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004357982,"about_ca_system_score_gemma":0.00001978002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001830289,"about_ca_topic_score_gemma":0.0009186602,"domain_scores_codex":[0.9991286,0.00002549476,0.0002680309,0.0002073832,0.0001051544,0.0002653268],"domain_scores_gemma":[0.9997551,0.00001553718,0.00004369261,0.00008461036,0.00003444798,0.00006662815],"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":[0.0001466941,0.0001354931,0.006771741,0.00003240897,0.00003822823,0.000107953,0.003952009,0.9849762,0.0003413452,0.0002584867,0.000625558,0.002613931],"study_design_scores_gemma":[0.0007871416,0.0003451914,0.020295,0.00004559137,0.00002354871,0.0001091883,0.0008130814,0.9773128,0.00006532091,0.00003906043,0.00002859891,0.00013548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780016,0.0008019914,0.0207323,0.00005699118,0.0000576637,0.0002400664,0.00003526577,0.00005176787,0.0000223468],"genre_scores_gemma":[0.9995562,0.00006215124,0.0002032246,0.000007813163,0.00009464654,0.00001058579,0.00005402562,0.000009411722,0.000001932489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0215546,"threshold_uncertainty_score":0.480627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493215309258469,"score_gpt":0.187399036548783,"score_spread":0.1724668834561983,"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."}}