{"id":"W4319211093","doi":"10.56248/marostek.v1i1.19","title":"Jaringan Syaraf Tiruan Memprediksi Tingkat Penggunaan Sosial Media Dimasa Pandemi Menggunakan Metode Backpropagation","year":2022,"lang":"id","type":"article","venue":"Jurnal Teknik Komputer Agroteknologi Dan Sains","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":"Humanities; Computer science; Art","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":[0.00113313,0.001794315,0.001128413,0.0009606549,0.0008715716,0.00268071,0.00139092,0.002041669,0.01188602],"category_scores_gemma":[0.003402108,0.000557152,0.0009358918,0.0008433721,0.0007151189,0.002689356,0.001121091,0.00251571,0.005894983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00110982,"about_ca_system_score_gemma":0.001854528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008217867,"about_ca_topic_score_gemma":0.008878645,"domain_scores_codex":[0.9992865,0.0001134062,0.00005489665,0.0002025912,0.0002324416,0.0001102055],"domain_scores_gemma":[0.9986978,0.0005114567,0.00007393199,0.0001119795,0.0005429951,0.00006185803],"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":[0.0006259484,0.0002646287,0.002590981,0.0006141664,0.0001996913,0.000452327,0.000356405,0.09287343,0.03887773,0.008774301,0.02047819,0.8338922],"study_design_scores_gemma":[0.00006528563,0.0002386728,0.002494613,0.0001960515,0.0001480477,0.000422649,0.0002800504,0.908428,0.04049369,0.01183786,0.03531263,0.00008232092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06066317,0.005850147,0.8839139,0.003267909,0.001884031,0.0002781593,0.0007987608,0.007600457,0.03574347],"genre_scores_gemma":[0.4847752,0.006701953,0.4050977,0.001732599,0.0007623417,0.0004755573,0.002059725,0.001403995,0.09699097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01188602,"threshold_uncertainty_score":0.03976274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02401643715459733,"score_gpt":0.2535587334676701,"score_spread":0.2295422963130728,"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."}}