{"id":"W3112291925","doi":"10.46880/methoda.vol9no3.pp156-164","title":"JARINGAN SYARAF TIRUAN MEMPREDIKSI LAJU PERTUMBUHAN PENDUDUK KOTA BINJAI METODE BACKPROPAGATION","year":2019,"lang":"id","type":"article","venue":"Majalah Ilmiah METHODA","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":"Forestry; Mathematics; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00115591,0.00161844,0.001063206,0.00108633,0.001025441,0.002309858,0.001310676,0.001567101,0.01124617],"category_scores_gemma":[0.003063954,0.0005688813,0.001153683,0.001357769,0.000627749,0.002534677,0.001343438,0.002143408,0.005683931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001232431,"about_ca_system_score_gemma":0.002218182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01290829,"about_ca_topic_score_gemma":0.01655394,"domain_scores_codex":[0.9992529,0.0001016472,0.00006335176,0.0001827846,0.0002863279,0.0001128941],"domain_scores_gemma":[0.998652,0.0003440685,0.00008771465,0.00013252,0.0007058776,0.0000778455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007314176,0.0004177273,0.01292104,0.001075788,0.0002904228,0.0007033592,0.0005937679,0.105934,0.03728897,0.007835916,0.03863844,0.7935691],"study_design_scores_gemma":[0.000119544,0.0004504422,0.02049241,0.0003983843,0.0003292979,0.0007110413,0.0008715541,0.7856993,0.07613878,0.01581357,0.0987689,0.0002067264],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2445586,0.007064517,0.6297227,0.006408678,0.002548044,0.0006789378,0.003693742,0.01141618,0.0939086],"genre_scores_gemma":[0.6485804,0.005443366,0.2302323,0.001104063,0.0003561126,0.0005281806,0.004420559,0.001180533,0.1081544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01290829,"threshold_uncertainty_score":0.03762221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02113525040026833,"score_gpt":0.2934320522441293,"score_spread":0.272296801843861,"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."}}