{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01625627,0.0004256723,0.0006143873,0.004887506,0.002792167,0.009919044,0.001729085,0.001336363,0.006055249],"category_scores_gemma":[0.04362196,0.0004326444,0.0006157626,0.003327176,0.001787352,0.01413092,0.005879817,0.001402458,0.002094914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258187,"about_ca_system_score_gemma":0.001611593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001614355,"about_ca_topic_score_gemma":0.00332068,"domain_scores_codex":[0.9919745,0.004809618,0.0006129789,0.0004857769,0.001925794,0.0001912401],"domain_scores_gemma":[0.9177193,0.06554455,0.002668078,0.007566755,0.005001215,0.001500082],"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":[0.0004896645,0.0005883213,0.01507281,0.00104012,0.000267991,0.001331085,0.01385781,0.006316803,0.005974689,0.1289277,0.1076555,0.7184775],"study_design_scores_gemma":[0.0002588694,0.0003480484,0.004301498,0.0003519993,0.0002578438,0.0008430137,0.006036987,0.1078752,0.01327649,0.1469966,0.7191707,0.0002826547],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1694697,0.003748096,0.6140895,0.05772857,0.004834236,0.001217824,0.001550581,0.02125959,0.1261019],"genre_scores_gemma":[0.6217462,0.001981943,0.3371639,0.003143988,0.002930614,0.0007716175,0.001566934,0.001080397,0.02961436],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01625627,"threshold_uncertainty_score":0.08597243,"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."}}