{"id":"W2985552643","doi":"","title":"Advanced Data Mining and Applications: 5th International Conference, ADMA 2009, Beijing, China, August 17-19, 2009: Proceedings","year":2009,"lang":"en","type":"article","venue":"Advanced Data Mining and Applications","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Beijing; China; Computer science; Chinese academy of sciences; Data science; Political 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005186052,0.0004296953,0.0003872874,0.0002419515,0.0009152265,0.0007888224,0.004681959,0.0001300127,0.00002582012],"category_scores_gemma":[0.00014381,0.0004541144,0.00002910262,0.0009267799,0.0002284291,0.003778819,0.002203329,0.0002610352,0.00001801534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000038225,"about_ca_system_score_gemma":0.0001516706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000214077,"about_ca_topic_score_gemma":0.00002290251,"domain_scores_codex":[0.9961138,0.00001917247,0.000682989,0.002214001,0.0004143212,0.0005557602],"domain_scores_gemma":[0.9955988,0.0001621198,0.0004679803,0.003140475,0.0002248471,0.0004058117],"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":[0.00000803848,0.000174211,0.0002608421,0.00002088999,0.00003246229,0.00000129146,0.0002421896,0.00001524939,0.000542173,0.03122575,0.02274797,0.9447289],"study_design_scores_gemma":[0.001025727,0.0001005747,0.002731951,0.0001408482,0.00007039968,0.0001066578,0.001010689,0.1291868,0.00006065821,0.002724624,0.8620458,0.0007952763],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003278376,0.002294985,0.9697115,0.004721821,0.0001125492,0.001647447,0.005308772,0.0007439943,0.01218052],"genre_scores_gemma":[0.03305744,0.002657149,0.9513406,0.0009855782,0.000488073,0.001167039,0.008753576,0.0000459347,0.001504666],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9439337,"threshold_uncertainty_score":0.9997911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04427514903601441,"score_gpt":0.3306492694076625,"score_spread":0.2863741203716481,"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."}}