{"id":"W1953706973","doi":"10.1007/s11192-016-2157-1","title":"Neophilia ranking of scientific journals","year":2016,"lang":"en","type":"article","venue":"Scientometrics","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Institute on Aging; University of Illinois at Chicago","keywords":"Ranking (information retrieval); Journal ranking; Information retrieval; Scientific literature; Computer science; Library science; Data science; Political science; Citation; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics","metaresearch"],"domain":"evaluation","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.002776265,0.0002908156,0.0008347271,0.02462912,0.001621043,0.004855945,0.000472651,0.0005417996,0.007349263],"category_scores_gemma":[0.02463008,0.0001592995,0.0005542001,0.01235043,0.0008260061,0.002002656,0.001695609,0.0005138642,0.001581304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001887861,"about_ca_system_score_gemma":0.001969032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001199243,"about_ca_topic_score_gemma":0.002808124,"domain_scores_codex":[0.9954669,0.00164678,0.0003175096,0.0003940412,0.001679892,0.0004947252],"domain_scores_gemma":[0.9793977,0.01054823,0.002361321,0.001474985,0.00461327,0.001604506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00185955,0.0003267227,0.4723831,0.001329611,0.001084442,0.0007058124,0.00143297,0.01145984,0.006481029,0.1190178,0.02601002,0.3579092],"study_design_scores_gemma":[0.0002591668,0.0006895536,0.6188802,0.0004700161,0.0006375738,0.001591665,0.004073293,0.1209612,0.01012746,0.2078314,0.03432963,0.0001489043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9128798,0.003567445,0.02141302,0.001769551,0.000290716,0.0001074149,0.003133873,0.0003584262,0.05647981],"genre_scores_gemma":[0.9922334,0.0003914662,0.00357503,0.0000425395,0.0001433355,0.00002762231,0.0009112667,0.00002175597,0.002653563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9753709,"threshold_uncertainty_score":0.02458572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7322136034264928,"score_gpt":0.6133548832507849,"score_spread":0.1188587201757079,"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."}}