{"id":"W2601582768","doi":"10.29173/slw6892","title":"Library Advocacy Through Twitter: A Social Media Analysis of #savelibraries and #getESEAright","year":2015,"lang":"en","type":"article","venue":"School Libraries Worldwide","topic":"Web and Library Services","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Public relations; Sociology; Social network analysis; World Wide Web; Internet privacy; Political science; Computer science","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":[0.001414048,0.0002363196,0.0002662945,0.004807948,0.002048576,0.003023162,0.0004509995,0.000762157,0.004835771],"category_scores_gemma":[0.009644987,0.0001948397,0.0003444013,0.007656026,0.0007190178,0.004735618,0.002421213,0.0008148231,0.00180749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001307096,"about_ca_system_score_gemma":0.001048374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0136265,"about_ca_topic_score_gemma":0.02444915,"domain_scores_codex":[0.9988261,0.00045391,0.0001154921,0.00009896627,0.0003101372,0.0001953932],"domain_scores_gemma":[0.9910644,0.00485431,0.001917703,0.0003354656,0.001277148,0.0005509984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005864403,0.0004201104,0.5924109,0.0006214468,0.0001305723,0.001265823,0.2384265,0.0003491522,0.002874054,0.008711014,0.02417085,0.1300331],"study_design_scores_gemma":[0.00001936927,0.0001357649,0.6312523,0.0002634362,0.0000929552,0.000467898,0.287824,0.002924922,0.001547914,0.001704892,0.07368481,0.00008166105],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9784168,0.0003135089,0.0006841914,0.002126052,0.00005631244,0.00008154467,0.002479745,0.00004549048,0.01579628],"genre_scores_gemma":[0.9836152,0.000628049,0.001503863,0.000549493,0.0001353244,0.0002486576,0.002843082,0.00009292152,0.01038341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0136265,"threshold_uncertainty_score":0.02709436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03001649161042922,"score_gpt":0.2419272922305024,"score_spread":0.2119108006200731,"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."}}