{"id":"W2059882478","doi":"10.1145/1394251.1394268","title":"The Fourth Asian Information Retrieval Symposium (AIRS 08)","year":2008,"lang":"en","type":"article","venue":"ACM SIGIR Forum","topic":"Web Data Mining and Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Beijing; Computer science; China; Library science; TRACE (psycholinguistics); Information retrieval; History; Linguistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002883637,0.0001097135,0.0001077318,0.00008537416,0.0007142585,0.0002599587,0.001801323,0.00005306597,0.000004975533],"category_scores_gemma":[0.0002886172,0.00007639416,0.00009041061,0.0005272602,0.00006722813,0.001553797,0.0005442452,0.0001327393,0.0003308468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002921375,"about_ca_system_score_gemma":0.00007116874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002227484,"about_ca_topic_score_gemma":0.000008578707,"domain_scores_codex":[0.9988337,0.00003567601,0.0002426297,0.0001716825,0.00036093,0.0003553832],"domain_scores_gemma":[0.9983428,0.0001189541,0.0001168301,0.001266081,0.0000722696,0.00008305477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008907174,0.0001319231,0.02064087,0.00003049358,0.0003702615,0.00008255569,0.01154058,0.0006396564,0.0008245439,0.08454736,0.4973388,0.3837639],"study_design_scores_gemma":[0.0009180502,0.0003182253,0.0110195,0.00003150097,0.0000464657,0.0002008263,0.001263519,0.06864263,0.003740031,0.005416719,0.907727,0.0006755549],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1294935,0.0004166694,0.5957599,0.2048914,0.003087813,0.0005538902,0.00006294476,0.001462181,0.06427165],"genre_scores_gemma":[0.9908025,0.000108496,0.007195586,0.0008504969,0.00007721825,0.00000456717,0.00002878366,0.000006123966,0.0009261728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.861309,"threshold_uncertainty_score":0.5493571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01092372813899535,"score_gpt":0.2161340161244162,"score_spread":0.2052102879854209,"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."}}