{"id":"W4385634227","doi":"10.33480/jitk.v9i1.4191","title":"PREDICTION PERFORMANCE OF AIRPORT TRAFFIC USING BILSTM AND CNN-BI-LSTM MODELS","year":2023,"lang":"en","type":"article","venue":"JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer)","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mean absolute percentage error; Computer science; Artificial neural network; Convolutional neural network; Artificial intelligence; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00103913,0.001862571,0.0005658654,0.001219073,0.000340043,0.0008904351,0.0007854317,0.0007567977,0.001866767],"category_scores_gemma":[0.002495837,0.0002928846,0.0007353444,0.0006397146,0.0002449655,0.001091087,0.0006888105,0.001135168,0.0008034713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104656,"about_ca_system_score_gemma":0.001186184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03560543,"about_ca_topic_score_gemma":0.0266711,"domain_scores_codex":[0.9997074,0.00004523411,0.00002400806,0.00009235047,0.00005439001,0.00007668318],"domain_scores_gemma":[0.999505,0.0001532095,0.00005596094,0.00002843277,0.0002103299,0.00004699889],"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":[0.0006256746,0.0002885635,0.03394018,0.0001855579,0.0002121932,0.0002424945,0.00006603674,0.8400649,0.006009409,0.0009934566,0.008073017,0.1092985],"study_design_scores_gemma":[0.000004726733,0.00003812802,0.001767142,0.000009464458,0.00001297046,0.00001107893,0.00001619802,0.9966881,0.001034063,0.0002294325,0.0001812765,0.000007522788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9420558,0.001953179,0.04121072,0.0007850744,0.0006968779,0.0000565671,0.002457113,0.003002897,0.007781798],"genre_scores_gemma":[0.9876093,0.0002935259,0.007127365,0.00007450522,0.00004757319,0.00002471661,0.002737347,0.00004892223,0.002036873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03560543,"threshold_uncertainty_score":0.07079637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07385314529668126,"score_gpt":0.2566660727148249,"score_spread":0.1828129274181437,"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."}}