{"id":"W2082736143","doi":"10.7152/nasko.v3i1.12790","title":"Social discovery tools: Cataloguing meets user convenience","year":2011,"lang":"en","type":"article","venue":"NASKO","topic":"Web and Library Services","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"World Wide Web; Computer science; Transaction log; Database transaction; Focus (optics); User satisfaction; Data science; Internet privacy; Database; Human–computer interaction","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":[0.01423928,0.0003743507,0.000793922,0.003783962,0.005122266,0.01550815,0.001431123,0.001488433,0.01221273],"category_scores_gemma":[0.06189689,0.0005712713,0.0006087532,0.005101302,0.002919112,0.01678343,0.007208723,0.0009873271,0.002944947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00192803,"about_ca_system_score_gemma":0.003612184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006227321,"about_ca_topic_score_gemma":0.007870289,"domain_scores_codex":[0.9847513,0.007537075,0.001026155,0.0008499636,0.005001597,0.0008339827],"domain_scores_gemma":[0.9450111,0.03473904,0.003465382,0.01055299,0.003956893,0.002274548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00117587,0.0004896781,0.1508629,0.001242731,0.000187976,0.001328842,0.06355567,0.000722487,0.009259982,0.06138806,0.01649076,0.693295],"study_design_scores_gemma":[0.0004243662,0.001478227,0.1975113,0.0006651693,0.0005948782,0.005972225,0.07494939,0.01499297,0.01059417,0.1046153,0.5877255,0.0004764957],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7172848,0.002414922,0.08514659,0.0108157,0.0001464087,0.0008276314,0.0006845308,0.004657811,0.1780216],"genre_scores_gemma":[0.9658294,0.000485122,0.02580973,0.000453687,0.0001697179,0.0001438751,0.0002497656,0.0002308532,0.0066278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9844918,"threshold_uncertainty_score":0.0753054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05582756286040792,"score_gpt":0.2381666132523515,"score_spread":0.1823390503919436,"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."}}