{"id":"W2135259798","doi":"10.5860/crl.61.3.234","title":"Patterns of Database Use in Academic Libraries","year":2000,"lang":"en","type":"article","venue":"College & Research Libraries","topic":"Web and Library Services","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Database; Academic library; Sample (material); Computer science; Online database; World Wide Web; Information retrieval; Library science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001420956,0.0001346823,0.0003861094,0.006403269,0.001163173,0.002417643,0.00101474,0.0005128246,0.002801794],"category_scores_gemma":[0.01211702,0.0002889616,0.0003460277,0.01112083,0.0008572074,0.001275023,0.00153749,0.0005624085,0.0007286998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003139678,"about_ca_system_score_gemma":0.002715545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.153491,"about_ca_topic_score_gemma":0.1848403,"domain_scores_codex":[0.9974195,0.0004321203,0.0004136119,0.0002849766,0.0008653618,0.0005843538],"domain_scores_gemma":[0.9855044,0.002961646,0.005262088,0.0004897898,0.003404529,0.002377501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001275213,0.00007314982,0.9867862,0.00004337469,0.00002963575,0.00008926651,0.00312731,0.00005450231,0.0002415078,0.000107363,0.0004810745,0.008839126],"study_design_scores_gemma":[0.000002319206,0.00003134086,0.9950165,0.00001247239,0.000007415204,0.0001525797,0.003961314,0.0001012978,0.0001227848,0.00002862361,0.000552713,0.00001071823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979565,0.0003110616,0.00004836453,0.0001688834,0.000001676976,0.000009324957,0.000472137,0.00001435092,0.001017787],"genre_scores_gemma":[0.998503,0.0003474756,0.00006223546,0.0000630677,0.000005449501,0.0000106129,0.0004148141,0.000006521776,0.0005868336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9975824,"threshold_uncertainty_score":0.3051951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09696913108164355,"score_gpt":0.3255264303986803,"score_spread":0.2285572993170368,"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."}}