{"id":"W4412740694","doi":"10.22329/jtl.v19i2.8932","title":"Integrating AI to Address Generational Characteristics and Educational Needs","year":2025,"lang":"en","type":"article","venue":"Journal of Teaching and Learning","topic":"AI in Service Interactions","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sociology; Data science; Computer science; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007855463,0.00006497343,0.0001080951,0.0002842263,0.0004643838,0.0003443712,0.000174096,0.00002626699,0.000007625799],"category_scores_gemma":[0.0008925715,0.00005698973,0.00002424566,0.0001173735,0.00001070567,0.0004398683,0.0001052399,0.001018352,0.000001401019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003543848,"about_ca_system_score_gemma":0.0001047127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002178683,"about_ca_topic_score_gemma":0.000002712334,"domain_scores_codex":[0.9992756,0.0001806697,0.0002521049,0.00008424834,0.0001242438,0.00008308524],"domain_scores_gemma":[0.9991122,0.0004532977,0.0001567298,0.00006049083,0.0001512695,0.00006599581],"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":[0.00003567084,0.0001598132,0.1042718,0.0000860246,0.0001742812,0.0000115109,0.0385341,0.003868184,0.01794265,0.2656702,0.009028917,0.5602169],"study_design_scores_gemma":[0.001088567,0.0007019088,0.3442123,0.002653931,0.0001087426,0.001638707,0.01034531,0.3244094,0.000455019,0.00758216,0.30604,0.0007639497],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5687338,0.00012736,0.4031411,0.02604939,0.00061563,0.00002637408,3.978152e-7,0.0000132684,0.001292743],"genre_scores_gemma":[0.9178563,0.000006064565,0.07896025,0.00179021,0.0002973434,0.000001210375,8.401362e-7,0.000003124586,0.001084714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.559453,"threshold_uncertainty_score":0.4424291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105907870432151,"score_gpt":0.310347810031819,"score_spread":0.2997570229886039,"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."}}