{"id":"W4288794301","doi":"10.26798/jiko.v5i2.645","title":"ANALISIS SENTIMEN PADA TWITTER TERHADAP PROGRAM KARTU PRA KERJA DENGAN RECURRENT NEURAL NETWORK","year":2021,"lang":"id","type":"article","venue":"JIKO (Jurnal Informatika dan Komputer)","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Humanities; 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":[0.0008347458,0.001192433,0.0005508943,0.001943544,0.0006883739,0.001705109,0.0006487296,0.000710497,0.007261083],"category_scores_gemma":[0.004796191,0.0002718766,0.000728888,0.00186733,0.0003243196,0.001803797,0.0006795627,0.001080983,0.003930707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007349874,"about_ca_system_score_gemma":0.0006482339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01261117,"about_ca_topic_score_gemma":0.0150916,"domain_scores_codex":[0.9991699,0.0001005548,0.00007491504,0.0002160837,0.0003049154,0.0001335413],"domain_scores_gemma":[0.9985119,0.0005882854,0.0001393013,0.0001210515,0.0005692129,0.00007027068],"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":[0.001881169,0.0005108728,0.2162732,0.001685432,0.0005583856,0.001979862,0.002326206,0.03844628,0.03231505,0.004443423,0.07659417,0.6229858],"study_design_scores_gemma":[0.00006003914,0.000740061,0.3071716,0.0003570182,0.0006673876,0.001367885,0.00513496,0.5585004,0.03822206,0.006528285,0.08100384,0.000246428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8459427,0.004527248,0.07399579,0.003427301,0.001299308,0.0003933782,0.02013183,0.006775325,0.04350723],"genre_scores_gemma":[0.9447771,0.00144809,0.0155605,0.0003013625,0.0002042784,0.0002526342,0.01221696,0.000268253,0.0249708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01261117,"threshold_uncertainty_score":0.02507555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684663541101455,"score_gpt":0.2788094299108612,"score_spread":0.2519627944998467,"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."}}