{"id":"W3150713369","doi":"10.29173/iasl7729","title":"Enhancing literacy and curriculum using digitalized collections and approaches","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Curriculum; Variety (cybernetics); Computer science; Information literacy; Subject (documents); Engineering ethics; Literacy; Curriculum development; Knowledge management; World Wide Web; Sociology; Public relations; Political science; Pedagogy; Engineering; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004281431,0.0003268493,0.0003938866,0.005604591,0.002204771,0.008100723,0.001568801,0.0007276734,0.01423982],"category_scores_gemma":[0.0100314,0.0002577723,0.0004101471,0.005106193,0.00255372,0.007019681,0.01129101,0.0011664,0.001846954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003257304,"about_ca_system_score_gemma":0.008341058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002425835,"about_ca_topic_score_gemma":0.006992403,"domain_scores_codex":[0.9967619,0.001693786,0.0002452054,0.0003030649,0.0007448514,0.0002510511],"domain_scores_gemma":[0.9953383,0.00215973,0.0004379183,0.001017173,0.000511107,0.0005356034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005700784,0.001016434,0.00387223,0.001005487,0.00002357169,0.0002012832,0.01993995,0.001716151,0.002086465,0.117462,0.01363087,0.8389886],"study_design_scores_gemma":[0.0001499689,0.0006264899,0.01413591,0.002519866,0.00008906403,0.0004215101,0.0307776,0.002222349,0.006838741,0.1208014,0.8213342,0.00008288699],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2018154,0.00475302,0.1610705,0.01372482,0.0005771024,0.002919041,0.0008045439,0.00170057,0.6126351],"genre_scores_gemma":[0.539085,0.009341854,0.3555216,0.002267192,0.000345844,0.003035176,0.0006649675,0.0002964619,0.08944182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01423982,"threshold_uncertainty_score":0.04763693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03830748169691753,"score_gpt":0.2905301113569849,"score_spread":0.2522226296600674,"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."}}