{"id":"W4402788292","doi":"10.18438/eblip30613","title":"Evidence Summary Theme: Community Engagement","year":2024,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Service-Learning and Community Engagement","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Theme (computing); Computer science; Data science; World Wide Web; Library science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.007070283,0.0001305178,0.0001038778,0.0001777579,0.002136469,0.00176873,0.0005447824,0.00008173249,0.0009135847],"category_scores_gemma":[0.004871429,0.0001243957,0.00004164068,0.0008345441,0.0001466725,0.2072418,0.0002981493,0.001234132,0.0002498429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003859336,"about_ca_system_score_gemma":0.0005613895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006543688,"about_ca_topic_score_gemma":0.000003654564,"domain_scores_codex":[0.9934731,0.005376474,0.0003201029,0.0001088857,0.0004906842,0.0002307476],"domain_scores_gemma":[0.9850329,0.01420618,0.0001355077,0.0004001265,0.00008688756,0.0001384438],"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":[0.0001991231,0.00008892097,0.0004150282,0.0006412085,0.00005124497,0.000008195221,0.03738923,0.0002035217,0.00002029386,0.727714,0.02524127,0.208028],"study_design_scores_gemma":[0.00006956185,0.0001015064,0.00093117,0.002187859,0.00004059711,0.000001883196,0.04106524,0.001287955,0.0001089102,0.0003056162,0.9537442,0.0001554616],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01501791,0.03151075,0.005415564,0.62137,0.001300306,0.001138719,0.0000143672,0.002140144,0.3220922],"genre_scores_gemma":[0.8276469,0.06072088,0.005020693,0.1039893,0.0002499769,0.00009180276,0.00006263972,0.0000194881,0.002198369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.928503,"threshold_uncertainty_score":0.9999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0872345607082085,"score_gpt":0.3365419248500465,"score_spread":0.249307364141838,"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."}}