{"id":"W7147658239","doi":"10.18572/2686-8598-2025-10-3-53-56","title":"From routine to creativity: how artificial intelligence is transforming the work of educators","year":2025,"lang":"","type":"article","venue":"Professor’s Journal Series Technical science","topic":"Artificial Intelligence in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Process (computing); Objectivity (philosophy); Test (biology); Matching (statistics); Applications of artificial intelligence; Work (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":["sts"],"category_scores_codex":[0.007172713,0.0006038703,0.0007963719,0.0007657895,0.003287074,0.002276186,0.008483367,0.0003239868,0.0002395135],"category_scores_gemma":[0.004446632,0.0004523388,0.0003618345,0.01344848,0.004670163,0.003627932,0.001693392,0.002014328,0.00006071887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008787936,"about_ca_system_score_gemma":0.004109471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002818976,"about_ca_topic_score_gemma":0.0002041418,"domain_scores_codex":[0.9922677,0.0004792319,0.002021161,0.001401459,0.002256474,0.001573934],"domain_scores_gemma":[0.9937254,0.001161664,0.0009962731,0.00177355,0.001684157,0.0006589856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002973237,0.000775051,0.001619051,0.00004310092,0.00005636329,0.000007800065,0.03748224,0.0001817876,0.03383291,0.09261271,0.001495823,0.8315958],"study_design_scores_gemma":[0.00003933463,0.0004963692,0.002275995,0.001532512,0.0001140669,0.00004572961,0.02038845,0.001353594,0.6722432,0.2956301,0.005193061,0.0006875873],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2090168,0.0005336601,0.5717794,0.209873,0.006978847,0.001078757,0.00001221016,0.00007734587,0.000650052],"genre_scores_gemma":[0.9715003,0.00026548,0.02535914,0.001203624,0.0006878405,0.00007808982,5.47153e-7,0.00002133558,0.0008836762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8309082,"threshold_uncertainty_score":0.9997928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05263166265361885,"score_gpt":0.3718309295752703,"score_spread":0.3191992669216515,"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."}}