{"id":"W4406413791","doi":"10.5539/jel.v14n3p115","title":"Bibliometric Analysis of Artificial Intelligence for Digital Literacy","year":2025,"lang":"en","type":"article","venue":"Journal of Education and Learning","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Literacy; Mathematics education; Psychology; Technological literacy; Artificial intelligence; Teaching method; Computer science; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.007818345,0.0005992628,0.001199421,0.1659962,0.001525343,0.006581115,0.0008599849,0.0008017424,0.005523769],"category_scores_gemma":[0.07377569,0.0002274425,0.001661417,0.2146257,0.0009132104,0.004343392,0.002365065,0.0006121151,0.001439768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002941571,"about_ca_system_score_gemma":0.005034546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006171486,"about_ca_topic_score_gemma":0.007629556,"domain_scores_codex":[0.9823546,0.003099756,0.003586314,0.001141518,0.009167818,0.0006499177],"domain_scores_gemma":[0.9166296,0.04523374,0.01674685,0.00352574,0.01645873,0.001405428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000187242,0.0001416883,0.5316025,0.01166118,0.001720875,0.0006975268,0.003854045,0.003826669,0.002026173,0.02947605,0.03705655,0.3777495],"study_design_scores_gemma":[0.00002494031,0.0001521135,0.7131587,0.003566716,0.001214829,0.002149505,0.005852581,0.007883364,0.002968594,0.01364703,0.2492133,0.0001682619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5971594,0.1110364,0.0126557,0.005822854,0.001157108,0.0006870913,0.1041116,0.001233282,0.1661365],"genre_scores_gemma":[0.9306537,0.02832014,0.008417984,0.0002293705,0.0007876097,0.0003912346,0.02690037,0.0001184979,0.004181119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8340038,"threshold_uncertainty_score":0.04134786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02168900841051916,"score_gpt":0.3752556725709275,"score_spread":0.3535666641604083,"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."}}