{"id":"W3128320926","doi":"","title":"JARINGAN SYARAF TIRUAN MEMPREDIKSI KEBUTUHAN OBAT-OBATAN MENGGUNAKAN METODE BACKPROPAGATION","year":2021,"lang":"id","type":"article","venue":"","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Backpropagation; Process (computing); Government (linguistics); Artificial neural network; Computer science; Layer (electronics); Autonomy; Artificial intelligence","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":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001050802,0.0005659935,0.0005617145,0.0002148014,0.0008631363,0.001338245,0.001860516,0.0002711124,0.0006160602],"category_scores_gemma":[0.0006175594,0.000591597,0.0002299003,0.001623702,0.0001562481,0.0009917166,0.001439663,0.0008605823,0.002607466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001835525,"about_ca_system_score_gemma":0.0006757737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005590682,"about_ca_topic_score_gemma":0.0002729628,"domain_scores_codex":[0.9950886,0.0005060209,0.0008330936,0.00182602,0.0008218932,0.0009243182],"domain_scores_gemma":[0.995401,0.0003519785,0.0003642753,0.002866807,0.0005027783,0.0005131731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004187,0.002022717,0.006521078,0.000548579,0.000897921,0.0003205192,0.01119827,0.001725783,0.04226052,0.4850912,0.07509585,0.3742757],"study_design_scores_gemma":[0.002041759,0.0005283254,0.01957594,0.0004188351,0.0004567569,0.0003133872,0.00113621,0.2463513,0.06191465,0.004431004,0.6602806,0.00255121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04057173,0.001042814,0.774222,0.01952096,0.002841904,0.0007939167,0.0001753246,0.0019161,0.1589152],"genre_scores_gemma":[0.8398685,0.0002305855,0.07570273,0.001471762,0.0008223927,0.00009852624,0.0009293077,0.00009759392,0.0807786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7992968,"threshold_uncertainty_score":0.9996985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01959398461914506,"score_gpt":0.2700725048600768,"score_spread":0.2504785202409317,"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."}}