{"id":"W2182378606","doi":"","title":"Universite de Montreal at TREC 2013: Experiments with Quantum Language Models in the Web Track.","year":2013,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Robustness (evolution); Computer science; Language model; Artificial intelligence; Focus (optics); Information retrieval; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01196033,0.002630054,0.001896585,0.001385499,0.002720298,0.002266593,0.003127241,0.00256919,0.01105106],"category_scores_gemma":[0.02092661,0.0007766219,0.001473482,0.002080713,0.0009778687,0.004066245,0.001840319,0.003653599,0.005702792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006045502,"about_ca_system_score_gemma":0.005000384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.291977,"about_ca_topic_score_gemma":0.3823018,"domain_scores_codex":[0.9944775,0.002832887,0.0002292022,0.0009008114,0.001057597,0.0005021073],"domain_scores_gemma":[0.9900803,0.005462933,0.0003278703,0.001480162,0.001578812,0.001069828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005400076,0.01121858,0.009376397,0.001905683,0.001277835,0.0004338104,0.000850266,0.06879713,0.008614266,0.00544503,0.646936,0.239745],"study_design_scores_gemma":[0.005223336,0.007532037,0.04993889,0.0004095506,0.0009850633,0.0004228171,0.001764853,0.7205356,0.02867185,0.01795079,0.1657602,0.0008050893],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6364254,0.02166127,0.06466748,0.009958145,0.006254591,0.006907433,0.1079313,0.04300958,0.1031847],"genre_scores_gemma":[0.6806932,0.002540616,0.08554547,0.002875383,0.0009148879,0.002669645,0.1702147,0.002097773,0.05244831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.291977,"threshold_uncertainty_score":0.580555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03172284299808632,"score_gpt":0.2476529462624022,"score_spread":0.2159301032643159,"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."}}