{"id":"W2416276544","doi":"","title":"[The biomedical periodicals of Hungarian editions--historical overview].","year":2006,"lang":"en","type":"article","venue":"PubMed","topic":"","field":"","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prestige; Publishing; Library science; Quarter (Canadian coin); Foreign language; Quality (philosophy); History; Computer science; Political science; Sociology; Linguistics; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001790102,0.0007273379,0.0008433227,0.02693079,0.001211868,0.004520215,0.001032343,0.0008336953,0.01997478],"category_scores_gemma":[0.006156716,0.00049654,0.0005700635,0.05538133,0.00131925,0.004187864,0.001667343,0.0007944196,0.009552075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00214318,"about_ca_system_score_gemma":0.00457213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005290751,"about_ca_topic_score_gemma":0.003350619,"domain_scores_codex":[0.9984891,0.0001894521,0.0004153366,0.0002226956,0.0005044917,0.0001789737],"domain_scores_gemma":[0.9920699,0.002007184,0.002092016,0.0003461082,0.002933006,0.0005516954],"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":[0.0002271855,0.00005627624,0.01418033,0.01270912,0.0001306473,0.0008996396,0.001308473,0.0002008097,0.0005655771,0.01098868,0.3261719,0.6325613],"study_design_scores_gemma":[0.000009737088,0.00004803488,0.06887348,0.004616228,0.0000912483,0.001902425,0.0008299854,0.00007329504,0.0003156515,0.001645472,0.9215573,0.00003719076],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0106661,0.917514,0.001153383,0.005172413,0.01036712,0.0001234019,0.01200358,0.0003467257,0.04265331],"genre_scores_gemma":[0.09929298,0.8186252,0.005772461,0.003863748,0.008162953,0.0002585074,0.0275423,0.0002377796,0.03624409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9730692,"threshold_uncertainty_score":0.06682223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437107101036904,"score_gpt":0.2250641563574571,"score_spread":0.2006930853470881,"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."}}