{"id":"W7135781364","doi":"","title":"Ranking national research systems by citation indicators:A comparative analysis using whole and fractionalized counting methods","year":2010,"lang":"en","type":"article","venue":"Research at the University of Copenhagen (University of Copenhagen)","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Economic and Social Research Council; National Natural Science Foundation of China; Genome Canada; National Research University Higher School of Economics; Russian Foundation for Basic Research; Stem Cell Network; National Science Foundation","keywords":"Ranking (information retrieval); Citation; Citation analysis; Key (lock); Information system; Comparative research","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.05573749,0.001049302,0.00454008,0.05149638,0.002431313,0.008151123,0.002593342,0.001327267,0.005939343],"category_scores_gemma":[0.1821275,0.0005058933,0.003683913,0.05548817,0.002178703,0.01400631,0.003792324,0.0009864545,0.0005232542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003839871,"about_ca_system_score_gemma":0.004648577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004971346,"about_ca_topic_score_gemma":0.005239523,"domain_scores_codex":[0.9456319,0.03193682,0.003377218,0.002610611,0.01461368,0.001829664],"domain_scores_gemma":[0.7666637,0.1773732,0.01175007,0.01611575,0.0257344,0.002362917],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004062882,0.0004871184,0.1441027,0.004558503,0.006662738,0.0001431914,0.003900132,0.01647609,0.00159201,0.0756977,0.005231376,0.7370856],"study_design_scores_gemma":[0.0006479524,0.003379254,0.5273418,0.002561956,0.01070879,0.0007368623,0.01522334,0.1735617,0.005397696,0.2244924,0.03520884,0.0007393429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8371143,0.02170561,0.1073485,0.001353199,0.0003368446,0.0004795546,0.002827068,0.0003814538,0.02845355],"genre_scores_gemma":[0.9176956,0.004231506,0.07355368,0.0001274087,0.0001512326,0.0002836926,0.002459157,0.0001364153,0.001361354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9485036,"threshold_uncertainty_score":0.2947715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6347261608904581,"score_gpt":0.6049857194261016,"score_spread":0.0297404414643565,"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."}}