{"id":"W4412877219","doi":"10.1145/3711896.3737849","title":"The 4th Workshop on AI Agent for Information Retrieval: Generating and Ranking","year":2025,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; University of California, San Diego; University of Illinois at Urbana-Champaign; University of Technology Sydney; Arizona State University; Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México; University of Illinois at Chicago; Tencent; Georgia Institute of Technology; Institute for Catastrophic Loss Reduction; National Science Foundation","keywords":"Ranking (information retrieval); Computer science; Information retrieval; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01555464,0.001890498,0.00252658,0.002183015,0.001947718,0.01134019,0.004691249,0.005044081,0.02418632],"category_scores_gemma":[0.01793153,0.00102906,0.003283298,0.002005687,0.002218187,0.008035092,0.005306328,0.007111315,0.01093939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00404147,"about_ca_system_score_gemma":0.004880816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005701424,"about_ca_topic_score_gemma":0.006195476,"domain_scores_codex":[0.9925559,0.003734881,0.0005240459,0.001263315,0.001215869,0.000705956],"domain_scores_gemma":[0.9886149,0.005350452,0.0002411273,0.001528501,0.002681961,0.001583115],"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":[0.0007276493,0.0007735618,0.0008292429,0.0008208514,0.0003100531,0.0004287106,0.00155737,0.01451214,0.003646872,0.07920577,0.5965058,0.300682],"study_design_scores_gemma":[0.0001642046,0.0003805789,0.0008674136,0.0005811218,0.0001342205,0.0003249459,0.0008107224,0.06886635,0.003938268,0.08676679,0.8370155,0.0001500583],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01426061,0.03903081,0.7508652,0.0709382,0.03731166,0.002008347,0.00261796,0.003762056,0.07920516],"genre_scores_gemma":[0.1435598,0.02314508,0.5245367,0.01411033,0.01923256,0.002658601,0.009757033,0.002508167,0.2604917],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02418632,"threshold_uncertainty_score":0.08226174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178067433191934,"score_gpt":0.2906828532696844,"score_spread":0.272876109950491,"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."}}