{"id":"W4372353049","doi":"10.18280/ijdne.180224","title":"System Analysis and Forecast of Yield Time Series Based on Neural Network Technologies","year":2023,"lang":"en","type":"article","venue":"International Journal of Design & Nature and Ecodynamics","topic":"Advanced Decision-Making Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Series (stratigraphy); Time series; Yield (engineering); Industrial engineering; Computer science; Engineering; Artificial intelligence; Machine learning; 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":[0.0003239892,0.0004771234,0.0004542235,0.000686864,0.0002486617,0.0006896585,0.0003652984,0.0003602123,0.00129943],"category_scores_gemma":[0.0008157659,0.0001580575,0.0004236644,0.0007122108,0.0002023938,0.0006755805,0.0002831978,0.0005189582,0.0002512661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00053826,"about_ca_system_score_gemma":0.0005250814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009120956,"about_ca_topic_score_gemma":0.006357935,"domain_scores_codex":[0.9998385,0.0000312753,0.00001526104,0.0000410516,0.00005909508,0.00001483029],"domain_scores_gemma":[0.9998623,0.00006454001,0.00002346872,0.000008879394,0.00003650132,0.000004330014],"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":[0.00004132966,0.00002644208,0.002119544,0.0001516232,0.00006424859,0.00009430332,0.00005611546,0.9005982,0.004148418,0.01027938,0.0007213525,0.0816991],"study_design_scores_gemma":[0.000001863668,0.000008615985,0.0006083529,0.000008387407,0.000007725906,0.000009955867,0.000006031172,0.9951317,0.0006196114,0.003065578,0.0005268836,0.000005328799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03155904,0.0009590065,0.9609581,0.0001921803,0.00006206216,0.00006073762,0.0002631643,0.0008489847,0.005096644],"genre_scores_gemma":[0.8595518,0.002012477,0.1329409,0.00004531377,0.0000755639,0.0002422502,0.000564191,0.00007577881,0.004491708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009120956,"threshold_uncertainty_score":0.01813573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01208114457783997,"score_gpt":0.2632997687243001,"score_spread":0.2512186241464601,"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."}}