{"id":"W2940936584","doi":"","title":"SIMULASI ANTRIAN PELAYANAN PADA GARDU TOL BINJAI","year":2019,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Urban Transport Systems Analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Toll; Transport engineering; Service (business); Computer science; Engineering; Business; Marketing","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":[0.0002254022,0.0004869138,0.0004800634,0.0004005141,0.0004219734,0.001210896,0.0006027386,0.0007803704,0.02410494],"category_scores_gemma":[0.001339796,0.0001882867,0.0005465872,0.000288233,0.0003728434,0.0007578362,0.0009019996,0.0007029096,0.003070631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006530271,"about_ca_system_score_gemma":0.0008289262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02198209,"about_ca_topic_score_gemma":0.01121431,"domain_scores_codex":[0.9998964,0.00002649251,0.000004718518,0.00002157955,0.00002865652,0.00002218382],"domain_scores_gemma":[0.9996675,0.0001608314,0.00002609947,0.00003253204,0.00009183161,0.00002109669],"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":[0.0001465558,0.0001204418,0.004717252,0.0003554487,0.00005746546,0.0004928662,0.0002227111,0.8034487,0.003216936,0.1390981,0.01911614,0.02900735],"study_design_scores_gemma":[0.00003363547,0.00003803878,0.001071988,0.00007810687,0.0000239914,0.0001802269,0.0001083598,0.9366259,0.001067838,0.02797949,0.03277478,0.00001758861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.211009,0.007055219,0.3733264,0.005348529,0.002483635,0.0002428783,0.0081024,0.002780088,0.3896519],"genre_scores_gemma":[0.8625251,0.002965444,0.04889932,0.0002598578,0.0002064607,0.0002421042,0.00238111,0.0004798828,0.08204065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02410494,"threshold_uncertainty_score":0.08063912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006543020932709964,"score_gpt":0.19888811247354,"score_spread":0.1923450915408301,"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."}}