{"id":"W7117252741","doi":"10.32038/ltrq.2025.52.03","title":"A Bibliometric Analysis of Practicum Research in Preservice Teacher Education: Trends, Themes, and Future Directions (2006–2024)","year":2025,"lang":"","type":"article","venue":"Language Teaching Research Quarterly","topic":"Teacher Education and Leadership Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Practicum; Thematic analysis; Identity (music); Citation; Teacher education; Quality (philosophy); Scopus","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":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01665196,0.0005998936,0.001952294,0.199577,0.001702337,0.006837461,0.001031625,0.0007121212,0.002368373],"category_scores_gemma":[0.06026698,0.0003817893,0.001947817,0.3099771,0.0009503229,0.004472049,0.002512098,0.000612936,0.0008116068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003441934,"about_ca_system_score_gemma":0.007682822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007483839,"about_ca_topic_score_gemma":0.01082011,"domain_scores_codex":[0.9799379,0.003526026,0.006269553,0.001380462,0.008139138,0.0007469615],"domain_scores_gemma":[0.9044034,0.0395978,0.0233128,0.004151181,0.02673752,0.001797263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004590367,0.0001586336,0.4911288,0.03800211,0.001584573,0.0007058161,0.01085248,0.0007591071,0.003315786,0.004984249,0.02510192,0.4229475],"study_design_scores_gemma":[0.00003534829,0.0002009363,0.8818012,0.005971958,0.0009101364,0.001289777,0.01157913,0.001105794,0.001766273,0.0009694647,0.09427445,0.00009556281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6914479,0.173002,0.004973861,0.005827696,0.0006813952,0.00115377,0.08499151,0.0007691905,0.03715277],"genre_scores_gemma":[0.8518379,0.08400527,0.0125545,0.0003486434,0.0006644791,0.001474882,0.04518208,0.0001434331,0.003788824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.800423,"threshold_uncertainty_score":0.08806503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1226793118059801,"score_gpt":0.5151390836230951,"score_spread":0.3924597718171151,"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."}}