{"id":"W4411234602","doi":"10.18438/eblip30642","title":"Library Chat Transcript Evaluation for User Sentiment During the COVID-19 Pandemic","year":2025,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"University of Toronto Scarborough; University of Toronto","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Computer science; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); World Wide Web; 2019-20 coronavirus outbreak; Virology; Medicine; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003070386,0.0003406709,0.0003214338,0.00178489,0.0009233007,0.001218474,0.0003093371,0.0003282455,0.002961922],"category_scores_gemma":[0.01717763,0.0001375051,0.0002753765,0.0009943064,0.0004108219,0.0008292751,0.0008802385,0.0004558179,0.001240955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186396,"about_ca_system_score_gemma":0.0009575037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007813346,"about_ca_topic_score_gemma":0.02112535,"domain_scores_codex":[0.9977322,0.001073167,0.0002006077,0.0002198695,0.000592782,0.0001813474],"domain_scores_gemma":[0.9797791,0.009971316,0.002140098,0.000507492,0.006748316,0.0008537511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.004718966,0.0005634932,0.4999471,0.00344071,0.000145553,0.001819459,0.1188695,0.001465322,0.073864,0.0008660081,0.03093427,0.2633656],"study_design_scores_gemma":[0.00005932348,0.0009700689,0.8827152,0.0003955787,0.0001393769,0.000616688,0.06259114,0.01539411,0.01543203,0.0004846754,0.02103682,0.000164913],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854121,0.0002033447,0.003780724,0.0003246949,0.00009509639,0.0004369031,0.003257067,0.0005076441,0.005982394],"genre_scores_gemma":[0.9817497,0.0001922707,0.009486393,0.0002065597,0.00007271645,0.0007109623,0.003377546,0.0001084985,0.004095356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9987815,"threshold_uncertainty_score":0.01623791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05292228128327673,"score_gpt":0.3644651186637181,"score_spread":0.3115428373804413,"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."}}