{"id":"W2032757407","doi":"10.1002/bult.2011.1720370408","title":"Using social discovery systems to leverage user‐generated metadata","year":2011,"lang":"en","type":"article","venue":"Bulletin of the American Society for Information Science and Technology","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Metadata; Cataloging; World Wide Web; Leverage (statistics); Computer science; Data science; Internet privacy; Information retrieval","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001224154,0.00006282668,0.0001296555,0.0001297607,0.00115802,0.0002368014,0.0005304153,0.00004971678,0.000005071345],"category_scores_gemma":[0.000484891,0.00005033545,0.00004983821,0.002552231,0.002197081,0.001123591,0.0001263981,0.00005619241,0.000002717628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001204667,"about_ca_system_score_gemma":0.0005674269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001352772,"about_ca_topic_score_gemma":0.00001920877,"domain_scores_codex":[0.9990523,0.00002763697,0.0002285739,0.0001133594,0.00037024,0.0002078257],"domain_scores_gemma":[0.9985965,0.00002646469,0.0003553246,0.0001704135,0.0008140095,0.00003728128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003172042,0.00005676789,0.001420433,0.00003313379,0.00004414012,2.429919e-8,0.03901729,0.00004378561,0.004824001,0.9106846,0.03371327,0.01013079],"study_design_scores_gemma":[0.00018475,0.00007163002,0.001671175,0.00001451466,0.00002834802,0.000001392003,0.165854,0.0002235715,0.003084408,0.0004601274,0.8282331,0.0001729279],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548591,0.0000333948,0.02021416,0.01898015,0.0006636744,0.001002123,0.00005419246,0.00009574639,0.00409742],"genre_scores_gemma":[0.9902035,0.00002180668,0.00778395,0.001364115,0.0000437805,0.00004167019,0.000001632253,0.000003005638,0.0005365594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9102245,"threshold_uncertainty_score":0.8906674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05343422760706387,"score_gpt":0.3259518859555743,"score_spread":0.2725176583485104,"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."}}