{"id":"W2747312054","doi":"","title":"短期en経路交通予測のためのネットワークに基づく動的航空交通流モデル【Powered by NICT】","year":2016,"lang":"ja","type":"article","venue":"Journal of Advanced Transportation","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Aeronautics; Aerospace engineering; Environmental science; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0001577081,0.0002591755,0.0002179563,0.0004608749,0.0008351651,0.001132958,0.0006061331,0.0003966355,0.01361097],"category_scores_gemma":[0.0003519586,0.0001523638,0.0002058032,0.0004080128,0.0005132459,0.0008895772,0.0006972778,0.0005633861,0.004155555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000839876,"about_ca_system_score_gemma":0.0005001349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001558486,"about_ca_topic_score_gemma":0.001815254,"domain_scores_codex":[0.9998404,0.00001128386,0.000006695369,0.00003424009,0.00007270192,0.00003473325],"domain_scores_gemma":[0.9998611,0.0000169961,0.0000176271,0.00001847688,0.00006841654,0.00001730928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004951514,0.0001719787,0.00583601,0.0007272197,0.00007208777,0.001406396,0.00123361,0.005262921,0.6095264,0.1609597,0.02977423,0.1845344],"study_design_scores_gemma":[0.00002633654,0.0001776484,0.005533412,0.0001222007,0.00008044484,0.001117683,0.001281999,0.02114227,0.6001667,0.01261511,0.3576548,0.00008142244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.341485,0.005552548,0.05172905,0.002233186,0.002247416,0.0002174697,0.0009977155,0.001118858,0.5944188],"genre_scores_gemma":[0.8561065,0.002322634,0.01360885,0.0004770544,0.0002527116,0.000201519,0.0005697823,0.000145449,0.1263155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01361097,"threshold_uncertainty_score":0.04553318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004916072688546676,"score_gpt":0.2133579776355112,"score_spread":0.2084419049469645,"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."}}