{"id":"W2158921918","doi":"","title":"York University at TREC 2006: Legal Track","year":2006,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Weighting; Track (disk drive); Computer science; Term (time); Information retrieval; Text retrieval; Probabilistic logic; Order (exchange); Domain (mathematical analysis); 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":[0.00005569436,0.00005419245,0.00005661821,0.00003404278,0.00008347938,0.00003985037,0.0004054011,0.00003093428,0.00009310224],"category_scores_gemma":[0.000001302225,0.00005250491,0.00003510892,0.000130548,0.00001309298,0.000237631,0.0001309613,0.00004268297,0.0001591401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006920766,"about_ca_system_score_gemma":0.00002417001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453354,"about_ca_topic_score_gemma":0.0007047665,"domain_scores_codex":[0.9994459,0.0000170685,0.00006596416,0.0002126822,0.0001099292,0.0001484287],"domain_scores_gemma":[0.999628,0.00001685856,0.00001869963,0.0002870846,0.0000138236,0.00003554753],"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":[0.000005940314,0.00006989483,0.003130623,0.000004502482,0.000006180607,0.00008325726,0.0001545687,0.003547605,0.0006254794,0.9075701,0.05991269,0.02488915],"study_design_scores_gemma":[0.0006593548,0.00003238053,0.00756087,0.000006102133,0.000006047381,0.00003298191,0.00004263394,0.3303912,0.0031734,0.002503115,0.6552482,0.0003436827],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08905434,0.00002732572,0.6792655,0.0009310331,0.0001654149,0.00003840119,8.297156e-7,0.0002207252,0.2302964],"genre_scores_gemma":[0.8054786,9.21343e-7,0.06417365,0.0001375587,0.00007394401,1.193887e-7,8.519993e-7,0.000002483727,0.1301318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.905067,"threshold_uncertainty_score":0.2197046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403716352911581,"score_gpt":0.185078277114786,"score_spread":0.1710411135856702,"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."}}