{"id":"W7087114786","doi":"10.52398/gjsd.2025.v5.i3.pp109-129","title":"Mapping Hungarian secondary school students’ digital and AI literacy with a focus on language learning","year":2025,"lang":"en","type":"article","venue":"GiLE Journal of Skills Development","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital literacy; Lifelong learning; Literacy; Information literacy; Computer literacy; Digital learning; Focus group","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005930648,0.0002168804,0.0002659233,0.002349452,0.0006894587,0.001200379,0.0002102322,0.000284114,0.003315675],"category_scores_gemma":[0.001386066,0.0001333896,0.0002587945,0.001841365,0.0005885283,0.0005812841,0.00123514,0.0003266114,0.0008680989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001236135,"about_ca_system_score_gemma":0.001386563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01860397,"about_ca_topic_score_gemma":0.03103229,"domain_scores_codex":[0.9996735,0.00004477865,0.00003470021,0.00006366624,0.00007394391,0.0001095545],"domain_scores_gemma":[0.99915,0.0001907541,0.0001864898,0.00004929931,0.0002695311,0.0001538925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001307603,0.0002464483,0.9212766,0.0001012374,0.00002819596,0.0002713073,0.0121147,0.0001636612,0.001279837,0.0009787815,0.001497546,0.06191096],"study_design_scores_gemma":[0.00000505675,0.0001136229,0.9843055,0.00003579225,0.00001305617,0.00008775958,0.01119848,0.0002086397,0.0005913847,0.0001828704,0.003249187,0.000008578972],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967894,0.00004775172,0.000223723,0.00003456058,0.000002968909,0.00002082113,0.0003785011,0.000005696802,0.002496601],"genre_scores_gemma":[0.9975224,0.00008521209,0.0004418522,0.0000522499,0.000002756346,0.00005841981,0.000603929,0.000004271165,0.001228967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01860397,"threshold_uncertainty_score":0.03699136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001584424307733091,"score_gpt":0.2623075271765592,"score_spread":0.2607231028688261,"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."}}