{"id":"W2115057477","doi":"","title":"York University at TREC 2006: Enterprise Email Discussion Search","year":2006,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Information retrieval; Thread (computing); Ranking (information retrieval); Search engine; Word (group theory); Document retrieval; Rank (graph theory); Query expansion; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007950339,0.001603596,0.001868663,0.00561936,0.003480827,0.002942711,0.001906436,0.002129144,0.04494273],"category_scores_gemma":[0.01570276,0.0006361064,0.0006544197,0.004326717,0.0005421361,0.004201123,0.001778739,0.002149923,0.02559722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003605829,"about_ca_system_score_gemma":0.003579342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05365471,"about_ca_topic_score_gemma":0.08222938,"domain_scores_codex":[0.9956963,0.001629493,0.0004465065,0.000531535,0.001234352,0.0004618245],"domain_scores_gemma":[0.9891411,0.003109242,0.0004747967,0.001440861,0.004506763,0.001327205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004872643,0.0006787258,0.001600734,0.0007829539,0.00006155766,0.0001073791,0.0003409448,0.00195333,0.005079172,0.001824119,0.8913915,0.09569229],"study_design_scores_gemma":[0.001570473,0.001243763,0.0301419,0.0003644905,0.0002012783,0.0003538704,0.00119057,0.06220024,0.03513097,0.007048899,0.8600481,0.0005055028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1995817,0.0146013,0.07025097,0.01538992,0.005443461,0.0104899,0.2711028,0.1040812,0.3090588],"genre_scores_gemma":[0.2144273,0.002169886,0.1344256,0.002136337,0.001065423,0.005800012,0.4089664,0.003307949,0.227701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05365471,"threshold_uncertainty_score":0.1503484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02514964510748901,"score_gpt":0.2407946580660498,"score_spread":0.2156450129585608,"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."}}