{"id":"W4409167433","doi":"10.1007/s44337-025-00290-0","title":"Research hotspots and publication trends of high flow nasal oxygen: a bibliometric analysis from 2004 to 2023","year":2025,"lang":"en","type":"article","venue":"Discover Medicine","topic":"Cardiovascular and Diving-Related Complications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lanzhou Science and Technology Bureau","keywords":"Environmental science; Bibliometrics; Computer science; Library 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":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.000951087,0.0001379977,0.0006279911,0.08198604,0.00008967292,0.00003153985,0.000171009,0.0001076264,0.0006400768],"category_scores_gemma":[0.001100473,0.0001092605,0.0001979321,0.2273849,0.0001644279,0.0000953312,0.0001275492,0.0002487837,0.00002618604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009153903,"about_ca_system_score_gemma":0.0001364306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005766832,"about_ca_topic_score_gemma":0.000128938,"domain_scores_codex":[0.9978799,0.00009981307,0.0004208684,0.0004785589,0.0008629247,0.0002579199],"domain_scores_gemma":[0.9977815,0.0003260927,0.00005991417,0.0009116178,0.0006828498,0.0002380507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001264622,0.001108771,0.1737897,0.0002845677,0.01883473,0.00004680287,0.00210369,0.001135995,0.01367549,0.00638125,0.4178,0.3635744],"study_design_scores_gemma":[0.002267583,0.0001558457,0.9891682,0.0001640349,0.002023414,0.000003103941,0.0002564895,0.0008607896,0.0002443704,0.0004055998,0.004364368,0.00008621527],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208739,0.0104972,0.0180077,0.02669984,0.0002009705,0.0004450447,0.0001604983,0.00005697098,0.02305783],"genre_scores_gemma":[0.9933603,0.0003024672,0.0003835607,0.0004329208,0.0001471448,0.00006104419,0.0006468118,0.00001162173,0.004654136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8153785,"threshold_uncertainty_score":0.9284189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03336999561882847,"score_gpt":0.3632489839949655,"score_spread":0.329878988376137,"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."}}