{"id":"W3097521102","doi":"10.5206/elip.v3i1.8580","title":"The Future Academic Librarian's Toolkit","year":2020,"lang":"en","type":"article","venue":"Emerging Library & Information Perspectives","topic":"Library Science and Information Literacy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; World Wide Web; Library science; Mathematics education; Data science; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0003262824,0.0001515855,0.0001187385,0.0001126135,0.001999916,0.001370631,0.0009630601,0.0001128227,0.001629601],"category_scores_gemma":[0.0002409536,0.0001129846,0.0001082065,0.00121378,0.0003211947,0.1328981,0.0001526254,0.0004201453,0.000762423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000256733,"about_ca_system_score_gemma":0.0004199487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009319851,"about_ca_topic_score_gemma":2.9949e-7,"domain_scores_codex":[0.9982241,0.0001188251,0.0004867049,0.0001466048,0.0006151215,0.0004086136],"domain_scores_gemma":[0.999068,0.0001372811,0.0002540046,0.0001842099,0.00006811594,0.0002884181],"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":[0.00002916271,0.000002977878,0.0007495651,0.000005681236,0.00000902527,2.513696e-7,0.2260231,0.00002793663,0.000001256878,0.6447065,0.1136219,0.01482262],"study_design_scores_gemma":[0.0001176355,0.00002025988,0.001686607,0.000006385412,0.000002238058,4.820315e-7,0.209188,0.0004850152,0.00003822235,0.001588572,0.7867316,0.0001350197],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01327106,0.001543636,0.000319371,0.6076673,0.00102759,0.0004503863,0.00002692772,0.0009594233,0.3747344],"genre_scores_gemma":[0.8161833,0.01264468,0.003046917,0.141245,0.01243187,0.0001024612,0.00026099,0.00005366692,0.01403116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8029122,"threshold_uncertainty_score":0.999666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029640356437659,"score_gpt":0.2576544460136895,"score_spread":0.2473580424493129,"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."}}