{"id":"W2825871937","doi":"10.5539/jas.v10n8p334","title":"A New Approach to Statistical Process Control: Identification of Outliers in Yield Maps","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Standard deviation; Control chart; Outlier; Statistical process control; Statistics; Productivity; Set (abstract data type); Control limits; Computer science; Mathematics; Process (computing)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00356985,0.0001081696,0.0003305561,0.0003279503,0.0001245459,0.0002112569,0.001348927,0.00003759273,0.00002873761],"category_scores_gemma":[0.01752475,0.00005798895,0.00004267833,0.002863256,0.0004270003,0.00120777,0.00006807859,0.0001946994,0.0000332594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001189023,"about_ca_system_score_gemma":0.0002685713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001817608,"about_ca_topic_score_gemma":0.0000107295,"domain_scores_codex":[0.9955274,0.00005499487,0.001241702,0.0003510546,0.002514508,0.0003103168],"domain_scores_gemma":[0.9962223,0.0007531721,0.0007642502,0.0001696292,0.001705253,0.0003853823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001009609,0.0007858678,0.04468715,0.00007862523,0.00003907116,0.000030527,0.01774023,0.03165429,0.6584786,0.03916062,0.01967929,0.1866562],"study_design_scores_gemma":[0.0006993324,0.0004812895,0.9250898,0.0001024242,0.00001913664,0.00008630571,0.006358353,0.001107397,0.0204928,0.04513622,0.0001690665,0.0002578915],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2890296,0.00001961632,0.7081876,0.0004497669,0.0005261393,0.0001766577,0.0000129924,0.000005598589,0.00159203],"genre_scores_gemma":[0.9639496,0.000001001338,0.03560571,0.00003646571,0.0002129873,0.000001708826,1.7899e-7,0.000002542327,0.0001897742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8804026,"threshold_uncertainty_score":0.990751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07254192081171536,"score_gpt":0.4028061477336383,"score_spread":0.330264226921923,"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."}}