{"id":"W2799220283","doi":"","title":"Tagging, Folksonomy and Co - Renaissance of Manual Indexing?","year":2007,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Folksonomy; Search engine indexing; The Renaissance; Information retrieval; Computer science; World Wide Web; Art; Art history","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002565961,0.0003074464,0.0004160972,0.0005088454,0.0004493876,0.0007298396,0.0004962904,0.0002322725,0.00005101155],"category_scores_gemma":[0.0004187243,0.0003369084,0.00008481699,0.0006107488,0.0005520157,0.01144337,0.0002425064,0.0002611347,0.0000752379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001963752,"about_ca_system_score_gemma":0.0002145943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009108171,"about_ca_topic_score_gemma":0.000004941905,"domain_scores_codex":[0.9968713,0.00005244777,0.001795036,0.0001900701,0.0004978946,0.0005932589],"domain_scores_gemma":[0.9968911,0.000208319,0.001692352,0.0003956476,0.0006250003,0.0001875412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002179245,0.00005041738,0.001632874,0.005083951,0.00005247961,0.000003704209,0.09057903,0.0002945959,0.0000345238,0.2942437,0.003493005,0.6045099],"study_design_scores_gemma":[0.002091305,0.0004909575,0.01205063,0.005975741,0.00007758025,0.0007469014,0.008828922,0.4941042,0.01812833,0.05374057,0.4021338,0.001631029],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04771026,0.001546588,0.8510199,0.0001789151,0.0009281485,0.000317526,0.00001189291,0.0001412568,0.0981455],"genre_scores_gemma":[0.9336145,0.0001043587,0.06469152,0.0006927605,0.0001709137,0.000007579979,0.00002412497,0.00001470645,0.0006795241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8859043,"threshold_uncertainty_score":0.9999083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159107776696999,"score_gpt":0.2706716383265426,"score_spread":0.2490805605595726,"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."}}