{"id":"W4392368523","doi":"10.1016/j.heliyon.2024.e27340","title":"The bibliometric analysis of extended reality in surgical training: Global and Chinese perspective","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Perspective (graphical); Virtual reality; Training (meteorology); Computer science; Geography; Human–computer interaction; Artificial intelligence","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":[],"category_scores_codex":[0.0005674897,0.00007425764,0.0002689573,0.006682024,0.00003149524,0.00002950765,0.00003136337,0.00005266398,0.0000916373],"category_scores_gemma":[0.0003962553,0.00004259828,0.0001283318,0.08569773,0.00008172332,0.00003569889,0.00001824384,0.0001160969,0.000002006059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006750825,"about_ca_system_score_gemma":0.00004276014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007934439,"about_ca_topic_score_gemma":0.000116218,"domain_scores_codex":[0.9991494,0.00006290719,0.0002185008,0.0001943306,0.000241352,0.0001334816],"domain_scores_gemma":[0.9990773,0.0006381131,0.00002516353,0.000110243,0.00006748951,0.00008172669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008262719,0.0002093661,0.5698513,0.0001972084,0.001410282,0.0005362959,0.003433689,0.0001964454,0.00002820389,0.0416774,0.000008445322,0.3816251],"study_design_scores_gemma":[0.0008520949,0.00005556447,0.9874946,0.00006508702,0.0002065453,0.00001741043,0.0007641917,0.007781548,0.000002306557,0.000612805,0.002102527,0.0000453519],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959761,0.01264038,0.00002888093,0.0008362992,0.00005314084,0.00008652303,0.00001188776,0.00003704783,0.02654485],"genre_scores_gemma":[0.998666,0.001171863,0.00001599668,0.00002764237,0.00004039674,0.000003035125,0.000006687726,0.000003812761,0.00006454001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4176433,"threshold_uncertainty_score":0.9337362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0537445807321134,"score_gpt":0.4006017006000203,"score_spread":0.3468571198679069,"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."}}