{"id":"W1618635184","doi":"10.18452/1272","title":"A Comparison of Social Tagging Designs and User Participation","year":2008,"lang":"en","type":"article","venue":"edoc Publication server (Humboldt University of Berlin)","topic":"Open Education and E-Learning","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Categorization; Computer science; World Wide Web; Resource (disambiguation); Social media; Collaborative filtering; Knowledge management; Data science; Recommender system; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002700865,0.00007498894,0.0001854417,0.0001588333,0.0003474118,0.00004638007,0.0004074253,0.0000598462,0.0001227974],"category_scores_gemma":[0.00004934795,0.0000960261,0.00004749997,0.0004674448,0.0001137479,0.001346294,0.0001478757,0.0001006919,0.00002253735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003361018,"about_ca_system_score_gemma":0.000137463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001161251,"about_ca_topic_score_gemma":0.00002116898,"domain_scores_codex":[0.9990752,0.000125608,0.0002096103,0.0002193957,0.0002326425,0.0001375177],"domain_scores_gemma":[0.9989104,0.00006135603,0.0003289166,0.0002054788,0.0004164706,0.00007740592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004849975,0.001049989,0.4328749,0.0001063619,0.0001096308,0.00000207931,0.1005229,0.0003536632,0.002949654,0.4187692,0.03461544,0.008597772],"study_design_scores_gemma":[0.000733542,0.00008647204,0.9188046,0.0000147275,0.0000256378,0.000003309452,0.005231665,0.01224286,0.001782368,0.0000963444,0.06076307,0.0002153662],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.94785,0.00001909563,0.04212539,0.003704663,0.00008738766,0.0001387837,0.000001535848,0.00007890676,0.005994226],"genre_scores_gemma":[0.989727,0.00001124907,0.008542223,0.00007280388,0.00001991481,4.190119e-7,0.0000177269,0.000003992796,0.001604674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4859298,"threshold_uncertainty_score":0.3915831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06428654432341561,"score_gpt":0.3022118980120965,"score_spread":0.2379253536886809,"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."}}