{"id":"W4387860954","doi":"10.1002/pra2.778","title":"Voices of the Stacks: A Multifaceted Inquiry into Academic Librarians' Tweets","year":2023,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Social Media and Politics","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Thematic analysis; Sentiment analysis; Classifier (UML); Library science; Point (geometry); Political science; Psychology; Sociology; Public relations; Computer science; Qualitative research; World Wide Web; Social science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001728599,0.0000529228,0.0001111358,0.0003463092,0.0007758527,0.00005827256,0.0007570349,0.0002284377,9.479226e-7],"category_scores_gemma":[0.013519,0.00003652713,0.00003637964,0.003976023,0.001159379,0.001746376,0.000206403,0.0001454792,0.000003790321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001397927,"about_ca_system_score_gemma":0.0003396804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007540844,"about_ca_topic_score_gemma":0.0000107967,"domain_scores_codex":[0.9986795,0.000008076835,0.0002990738,0.00007631395,0.0006878746,0.0002491512],"domain_scores_gemma":[0.9977254,0.0001972263,0.0007250223,0.00005932082,0.001261131,0.00003194292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.000005936021,0.000008213236,0.3941439,0.00007651633,0.00001629381,1.84676e-9,0.1820491,0.000001457956,0.007737346,0.4051287,0.003309892,0.007522557],"study_design_scores_gemma":[0.0008511735,0.00007927416,0.08314747,0.0001297145,0.00005865182,3.761351e-7,0.409007,0.0004925699,0.145935,0.1608853,0.1991748,0.0002385473],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977862,0.000009879194,0.000002083086,0.01830711,0.0005354162,0.0004476325,0.000008920649,0.00009069472,0.002736276],"genre_scores_gemma":[0.9994798,0.00006738639,0.00006846485,0.0001385242,0.00004795411,0.0000362583,6.797725e-7,0.000002239111,0.0001587504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3109965,"threshold_uncertainty_score":0.9947906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02503192006893222,"score_gpt":0.3241964975651281,"score_spread":0.2991645774961958,"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."}}