{"id":"W4388115096","doi":"10.18438/b8863","title":"Small Library Research: Using Qualitative and User-Oriented Research to Transform a Traditional Library into an Information Commons","year":2017,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Library Science and Administration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Space (punctuation); World Wide Web; Meaning (existential); Commons; Library instruction; Information literacy; Value (mathematics); Library science; Psychology; Political 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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.1090267,0.0004803982,0.0006149322,0.003661356,0.007608933,0.008451775,0.003375982,0.001557744,0.003674512],"category_scores_gemma":[0.09831673,0.0006588337,0.0004421797,0.003631783,0.01240742,0.009409358,0.008154177,0.002113562,0.0005466497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009045693,"about_ca_system_score_gemma":0.01140089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002693038,"about_ca_topic_score_gemma":0.004764382,"domain_scores_codex":[0.8476069,0.1434916,0.001990461,0.001655074,0.003457046,0.001798904],"domain_scores_gemma":[0.765699,0.2128498,0.004068154,0.00769511,0.007052856,0.002635071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001972446,0.0004992827,0.004217186,0.001198614,0.00002753854,0.0005100713,0.9184307,0.0002588319,0.001903822,0.01440713,0.002533752,0.05581577],"study_design_scores_gemma":[0.000123722,0.0008185026,0.003666228,0.001324999,0.00003688149,0.0002237999,0.9462197,0.0009469928,0.003508883,0.01077843,0.03231099,0.00004089251],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8927045,0.001697727,0.05528588,0.009479924,0.0002910841,0.007295314,0.000346565,0.0002832786,0.03261557],"genre_scores_gemma":[0.9641952,0.0006981056,0.02512346,0.001433568,0.00004103722,0.004928181,0.00009149924,0.00007886119,0.003410093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9915482,"threshold_uncertainty_score":0.5765952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.355379801779495,"score_gpt":0.4758192823923528,"score_spread":0.1204394806128579,"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."}}