{"id":"W3166733659","doi":"10.56042/alis.v68i2.40763","title":"A scientometric analysis and visualization of the 50 highly cited papers of Eugene Garfield","year":2022,"lang":"en","type":"article","venue":"Annals of Library and Information Studies","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Informetrics; Citation; Scientometrics; Citation analysis; Bibliometrics; Popularity; Library science; Psychology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.003803183,0.000064325,0.0002967263,0.0485283,0.0002625918,0.0001543502,0.0004935237,0.00002304907,0.0001639075],"category_scores_gemma":[0.003990402,0.00003863024,0.0001081732,0.2372985,0.0002562724,0.003264971,0.001157264,0.0000560582,3.422149e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002287306,"about_ca_system_score_gemma":0.00004206711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007447609,"about_ca_topic_score_gemma":2.233237e-7,"domain_scores_codex":[0.9961482,0.0001567532,0.0007596401,0.0001263965,0.002682536,0.0001265168],"domain_scores_gemma":[0.9968399,0.001417649,0.0006843604,0.0002316916,0.0007699956,0.00005639187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001061791,0.0001135399,0.895376,0.0001090127,0.0005861511,1.71666e-7,0.004184318,0.0008426391,0.0005189978,0.0252446,0.01211878,0.06079966],"study_design_scores_gemma":[0.0002589713,0.0003067358,0.9424835,0.00000829802,0.00004387837,5.968862e-7,0.006543562,0.002335554,0.01232831,0.001212132,0.03439262,0.0000858258],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879799,0.004170686,0.000131844,0.001697102,0.00009367747,0.0001314954,0.0001052914,0.000005587986,0.00568445],"genre_scores_gemma":[0.9934959,0.005673332,0.00006760727,0.0004459992,0.000004048152,0.000004667804,0.000005745121,0.000001386499,0.0003012719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1887702,"threshold_uncertainty_score":0.9622558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4622953995903732,"score_gpt":0.5310908397427637,"score_spread":0.06879544015239047,"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."}}