{"id":"W4403100976","doi":"10.1590/scielopreprints.10128","title":"Approaching bibliometrics and prosopography: The comprehensive publishing landscape of CNPq (Brazil) and CONICET (Argentina) and its coverage in global databases","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Literary and Cultural Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consejo Nacional de Investigaciones Científicas y Técnicas; Agence Universitaire de la Francophonie; L'Oreal USA","keywords":"Prosopography; Bibliometrics; Publishing; Geography; Regional science; Database; Library science; Political science; Computer science; Archaeology; Law","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01171811,0.0006190473,0.001125352,0.04675132,0.00188814,0.00999526,0.0009168573,0.0005964478,0.004114407],"category_scores_gemma":[0.05584677,0.0002776993,0.0003855152,0.1284508,0.003242143,0.00718469,0.004410815,0.0006723176,0.0007298834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00369675,"about_ca_system_score_gemma":0.005250833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01389074,"about_ca_topic_score_gemma":0.01379958,"domain_scores_codex":[0.9849762,0.005707845,0.001630182,0.001632465,0.005532584,0.0005206663],"domain_scores_gemma":[0.9680777,0.01661971,0.004919382,0.002709643,0.007073207,0.0006002724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000146696,0.0001153589,0.1919254,0.007280048,0.0004049735,0.0007825643,0.05374246,0.0019253,0.002022268,0.230755,0.01398798,0.4969119],"study_design_scores_gemma":[0.0000407985,0.0001620969,0.4942659,0.004099112,0.0003495295,0.001820617,0.08356152,0.006662962,0.002632961,0.1094546,0.2968081,0.0001418042],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6410092,0.04173753,0.07026329,0.01013764,0.0005204019,0.0007189019,0.02038077,0.0003777711,0.2148546],"genre_scores_gemma":[0.9539257,0.009589025,0.02536255,0.0003298444,0.0003194262,0.0007501607,0.005709874,0.0001479817,0.003865457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9532487,"threshold_uncertainty_score":0.06197202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07457270567631333,"score_gpt":0.3438457829873288,"score_spread":0.2692730773110155,"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."}}