{"id":"W4413183453","doi":"10.1080/24750158.2025.2542433","title":"Shaping the Global Future of Library and Information Science Education: Lessons Learned from the Web-based Information Science Education (WISE) Consortium and Other International Collaborations","year":2025,"lang":"en","type":"article","venue":"Journal of the Australian Library and Information Association","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information science; Library science; Web of science; Political science; Engineering ethics; Knowledge management; World Wide Web; Data science; Computer science; Engineering; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001492935,0.0001310038,0.0001464577,0.000457872,0.001674055,0.002776611,0.0009032607,0.0001148444,0.00006865428],"category_scores_gemma":[0.0008718322,0.0000830737,0.00005760253,0.002891213,0.000894729,0.2271246,0.0001707324,0.0002560616,0.000003280088],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001303146,"about_ca_system_score_gemma":0.008489156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002978781,"about_ca_topic_score_gemma":0.000002327081,"domain_scores_codex":[0.9976743,0.0001916303,0.0009279205,0.0000885751,0.0009084638,0.0002090686],"domain_scores_gemma":[0.9970339,0.0002562231,0.001877528,0.0002088448,0.0005025957,0.0001208951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004554625,0.00002532784,0.08526786,0.00002381719,0.00002103289,9.43638e-9,0.008284192,0.00006088724,0.00002085913,0.8620195,0.01349497,0.03073598],"study_design_scores_gemma":[0.0003756596,0.00001965141,0.2313206,0.000130505,0.00002718908,0.000002064427,0.02088879,0.0006063411,0.0002533772,0.005277998,0.7410047,0.00009313001],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3318124,0.0002074748,0.0001147514,0.6060963,0.004057245,0.0008071198,0.0002805584,0.00005481681,0.0565693],"genre_scores_gemma":[0.9578222,0.001390618,0.001157584,0.03846749,0.0004281421,0.00001343941,0.0000673304,0.000003567091,0.0006495922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8567415,"threshold_uncertainty_score":0.9996256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851447685552176,"score_gpt":0.3040170162432851,"score_spread":0.2855025393877634,"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."}}