{"id":"W2969753381","doi":"10.1155/2019/4183065","title":"Dynamic Changes in Maritime Research Capability in Chinese Universities","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"China; Mainland China; Ranking (information retrieval); Government (linguistics); Regional science; Geography; Political science; Economy; Business; Economics; Computer science; Archaeology","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002434541,0.0002031244,0.0003126128,0.01150303,0.001054903,0.002745028,0.0004590389,0.0003467936,0.002994046],"category_scores_gemma":[0.01067894,0.0001503092,0.0003889433,0.01749071,0.0005450207,0.00168582,0.001539854,0.0002122497,0.0004435416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003078746,"about_ca_system_score_gemma":0.005024217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02490567,"about_ca_topic_score_gemma":0.02806163,"domain_scores_codex":[0.9980106,0.0002292308,0.0002762347,0.0002515021,0.0007167783,0.000515706],"domain_scores_gemma":[0.9860384,0.002321355,0.003853623,0.0004738419,0.004301828,0.003010997],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007650622,0.00002723113,0.9661477,0.0001217572,0.00007826489,0.0003933299,0.003697476,0.000606955,0.0009619106,0.001681538,0.001346042,0.02486134],"study_design_scores_gemma":[0.000003609123,0.00002819894,0.9926352,0.00002714163,0.00002980931,0.0001041874,0.003663744,0.0005147862,0.0002543519,0.0002130293,0.002513739,0.00001222861],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909618,0.0009035643,0.0001590848,0.0005298819,0.00002059821,0.00001019333,0.0006591713,0.00001948868,0.006736082],"genre_scores_gemma":[0.9984013,0.0003472965,0.00007411779,0.00002774502,0.00001497841,0.000006363966,0.0002959116,0.000002669896,0.0008295243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9975654,"threshold_uncertainty_score":0.04952145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008781230240426175,"score_gpt":0.2684830498932032,"score_spread":0.2597018196527771,"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."}}