{"id":"W3013512521","doi":"10.18438/eblip29654","title":"Engineering Students and Professionals Report Different Levels of Information Literacy Needs and Challenges","year":2020,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Likert scale; Medical education; Information literacy; Sample (material); Literacy; Psychology; Scale (ratio); Library science; Engineering; Mathematics education; Computer science; Medicine; Pedagogy; Geography","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":[0.004614281,0.0002857263,0.0005564004,0.002776401,0.001295624,0.003698817,0.0004591341,0.001408722,0.00654113],"category_scores_gemma":[0.02921574,0.0003532096,0.0004589468,0.001650987,0.001527672,0.003766978,0.004111467,0.0009721381,0.001490537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005406567,"about_ca_system_score_gemma":0.001110823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001602002,"about_ca_topic_score_gemma":0.002082005,"domain_scores_codex":[0.9949155,0.001093514,0.0006925828,0.0004091234,0.002101221,0.0007882323],"domain_scores_gemma":[0.9766272,0.01219206,0.004450589,0.0006813272,0.003440435,0.002608489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001989989,0.0004801986,0.6425146,0.0009078063,0.0001082285,0.0009588144,0.1786875,0.0001333691,0.001866119,0.002324941,0.006229552,0.1655899],"study_design_scores_gemma":[0.00002951329,0.0005682446,0.5398775,0.0009908581,0.00005493648,0.004597741,0.4089442,0.000318909,0.0008855576,0.004975448,0.03860123,0.0001559158],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9803501,0.002278856,0.0007665035,0.003255029,0.00006044543,0.0000465219,0.0001789732,0.00003115924,0.01303244],"genre_scores_gemma":[0.9923235,0.001704346,0.0007363432,0.001477502,0.00003299221,0.00005891298,0.0002401721,0.00001493719,0.003411305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00654113,"threshold_uncertainty_score":0.02440292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04271385876638752,"score_gpt":0.323303559448108,"score_spread":0.2805897006817205,"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."}}