{"id":"W2959600099","doi":"10.35724/mustek.v7i2.911","title":"ANALISIS AKSESIBILITAS TRANSPORTASI INTERNAL & EKSTERNAL KABUPATEN MERAUKE SEBAGAI SALAH SATU WILAYAH PERBATASAN NKRI – PNG","year":2018,"lang":"id","type":"article","venue":"MUSTEK ANIM HA","topic":"Economic Growth and Fiscal Policies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Geography; Forestry","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":[0.001194854,0.0003475641,0.0004312102,0.001567427,0.0008310387,0.002551493,0.0005683093,0.0005580617,0.01434655],"category_scores_gemma":[0.002958489,0.0002633543,0.0009007173,0.002070077,0.0004275569,0.0008399872,0.001337084,0.0008999406,0.002475755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001616233,"about_ca_system_score_gemma":0.002320761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06197863,"about_ca_topic_score_gemma":0.07204165,"domain_scores_codex":[0.9990245,0.0001870106,0.0001052234,0.0001693517,0.0003044803,0.0002093089],"domain_scores_gemma":[0.9978364,0.0005964012,0.0004848555,0.0001153212,0.0007768848,0.0001901481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002907221,0.000132991,0.9234187,0.0007957633,0.0002312953,0.0006201117,0.005262048,0.0002821734,0.001400817,0.001343991,0.008361121,0.05786021],"study_design_scores_gemma":[0.000009365142,0.0001630971,0.9534773,0.000558503,0.0001585841,0.0004262469,0.01543889,0.0004517175,0.001446935,0.0004251271,0.02741505,0.00002926062],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9246787,0.003839712,0.002055997,0.0015197,0.0001182844,0.0002754991,0.01659924,0.00008833607,0.0508246],"genre_scores_gemma":[0.9503645,0.003192137,0.001973454,0.0004530874,0.00005604669,0.0003360128,0.005767256,0.00004387102,0.03781356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06197863,"threshold_uncertainty_score":0.1232358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04284607573792458,"score_gpt":0.2432461184603704,"score_spread":0.2004000427224459,"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."}}