{"id":"W7131881348","doi":"10.5281/zenodo.18796691","title":"Teacher Digital Competency's Longitudinal Impact on Student Academic Performance in Kenyan Schools Revisited,","year":2004,"lang":"en","type":"article","venue":"Open MIND","topic":"Digital literacy in education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Kenya; Sample (material); Longitudinal study; Literacy; Technological literacy; Longitudinal data; Qualitative property; Test (biology); Qualitative research","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005015545,0.00022283,0.0003066226,0.001093014,0.001259297,0.001381809,0.0003866724,0.0003407667,0.002141665],"category_scores_gemma":[0.01496368,0.0002165742,0.0003671563,0.001311054,0.0006852752,0.00118378,0.001390759,0.0007929017,0.0003343181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001333481,"about_ca_system_score_gemma":0.002602197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04183853,"about_ca_topic_score_gemma":0.06811365,"domain_scores_codex":[0.9985737,0.0005853754,0.0001208901,0.0001956022,0.0002942903,0.0002301882],"domain_scores_gemma":[0.9924976,0.002368852,0.002515755,0.0006558284,0.001273241,0.0006887238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006822752,0.0001170487,0.9854314,0.00002992194,0.00003468237,0.00008799523,0.003479336,0.0001155036,0.0001788667,0.0001966862,0.0001427949,0.01011746],"study_design_scores_gemma":[0.000002045016,0.0001009109,0.9967584,0.00003111274,0.00002086817,0.00005979526,0.001963624,0.0001542897,0.0001985476,0.00006045956,0.0006448327,0.000005093111],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982772,0.0003023394,0.0001211889,0.0001940426,0.000008846077,0.000006812837,0.0001485189,0.000003087616,0.0009381514],"genre_scores_gemma":[0.9992456,0.0001291241,0.0001171967,0.0000188467,0.000003706774,0.000008997841,0.0001180603,0.000001265011,0.0003571949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04183853,"threshold_uncertainty_score":0.08319002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066839886167962,"score_gpt":0.3561242457829686,"score_spread":0.325455846921289,"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."}}