{"id":"W1979392992","doi":"10.1145/2009916.2010060","title":"Parallel learning to rank for information retrieval","year":2011,"lang":"en","type":"article","venue":"","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Learning to rank; Ranking (information retrieval); Rank (graph theory); Computer science; Machine learning; Ranking SVM; Information retrieval; Scale (ratio); Artificial intelligence; Data mining; Mathematics","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":[0.0004048278,0.00006643341,0.00007178889,0.0001418615,0.0001379347,0.0001289723,0.0003937337,0.00003913623,0.0000795229],"category_scores_gemma":[0.0001364975,0.00005412544,0.00004670869,0.0003131543,0.000008761037,0.002075265,0.0001044174,0.00007626067,0.0006922944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002096701,"about_ca_system_score_gemma":0.00004212462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000146725,"about_ca_topic_score_gemma":6.96689e-7,"domain_scores_codex":[0.9992398,0.000014283,0.0002230851,0.0000799013,0.0002249469,0.0002179681],"domain_scores_gemma":[0.9994146,0.00003063882,0.00004705933,0.0001625476,0.000231779,0.0001133356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004757837,0.00006524219,0.0009262848,0.00005287091,0.00001717395,0.000001604057,0.03665003,0.0003578126,0.0003525377,0.713385,0.007643279,0.2400723],"study_design_scores_gemma":[0.004242084,0.002739928,0.03635523,0.00003080547,0.00001665293,0.00002734796,0.001649107,0.2429297,0.03793384,0.005072128,0.6677941,0.001209057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008405186,0.000001211471,0.9669836,0.0002725421,0.0001536459,0.0003781961,0.000001065129,0.0001925548,0.02361206],"genre_scores_gemma":[0.5047988,0.000003433242,0.4890454,0.002211732,0.00003853201,0.00004763354,0.00001526453,0.000005287329,0.003833919],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7083129,"threshold_uncertainty_score":0.8898275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04381466520199773,"score_gpt":0.26896191400584,"score_spread":0.2251472488038423,"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."}}