{"id":"W2126750612","doi":"10.1002/meet.2011.14504801069","title":"Social tagging &amp; folksonomies: Indexing, retrieving… and beyond?","year":2011,"lang":"en","type":"article","venue":"Proceedings of the American Society for Information Science and Technology","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Western University","funders":"","keywords":"Folksonomy; Computer science; Search engine indexing; Information retrieval; World Wide Web; Data science","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":[0.00757718,0.0005478702,0.001006672,0.006491215,0.002998015,0.01466791,0.001337234,0.002289227,0.01194356],"category_scores_gemma":[0.01574146,0.0004357307,0.0005871856,0.01145601,0.003569466,0.02419548,0.002817819,0.001571634,0.00662841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001797949,"about_ca_system_score_gemma":0.001703278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002966454,"about_ca_topic_score_gemma":0.004334368,"domain_scores_codex":[0.9950059,0.002789921,0.0003660283,0.0004160518,0.001199566,0.0002226025],"domain_scores_gemma":[0.9892681,0.00491948,0.000577268,0.001530808,0.003325474,0.0003788012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00008867968,0.00007486795,0.003126333,0.000831995,0.0000589221,0.0001473899,0.00301313,0.001016336,0.004413098,0.1287117,0.2170707,0.6414468],"study_design_scores_gemma":[0.00001140395,0.00004227129,0.002970166,0.000990162,0.00003806363,0.000494,0.004965116,0.007943479,0.004121522,0.1291031,0.8492252,0.00009558971],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05148067,0.0753295,0.5195357,0.1221133,0.01192963,0.0005767187,0.002750495,0.004151202,0.2121328],"genre_scores_gemma":[0.3951678,0.09511576,0.3121485,0.0149147,0.01183331,0.0005394811,0.006802226,0.002187559,0.1612906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01466791,"threshold_uncertainty_score":0.04007244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429762885341989,"score_gpt":0.2606197474445394,"score_spread":0.2363221185911195,"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."}}