{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002295495,0.0001623019,0.0001605109,0.00008109822,0.00009287658,0.0001734627,0.001134401,0.00007144875,0.0001319897],"category_scores_gemma":[0.0000110834,0.0001124363,0.00003435449,0.0002852616,0.00005887452,0.0007029246,0.0001859921,0.0001987869,0.0001079886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001292426,"about_ca_system_score_gemma":0.0001533815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003511953,"about_ca_topic_score_gemma":0.0006090933,"domain_scores_codex":[0.9985873,0.0001320793,0.0001632646,0.0003800364,0.0003552803,0.0003820401],"domain_scores_gemma":[0.9990407,0.00009126947,0.0000704307,0.0006330835,0.00007009361,0.00009438732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007749993,0.001024949,0.01245157,0.0001282803,0.0001756867,0.001244432,0.3941232,0.01424425,0.07769018,0.3898643,0.007547061,0.100731],"study_design_scores_gemma":[0.0007276428,0.0001060831,0.003639833,0.00003651092,0.000005657828,0.00002522508,0.001751025,0.9895027,0.001373787,0.002511741,0.00009968645,0.0002201433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8959514,0.0001823165,0.09435176,0.000891378,0.00004271046,0.0002821711,0.000002123303,0.00008332227,0.008212755],"genre_scores_gemma":[0.995407,0.00003595839,0.002962142,0.0002242598,0.00001987817,0.000008177424,0.000002041397,0.000007449372,0.00133303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9752584,"threshold_uncertainty_score":0.5309047,"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."}}