{"id":"W1888011339","doi":"","title":"Clinical Information Retrieval using Document and PICO Structure","year":2010,"lang":"en","type":"article","venue":"North American Chapter of the Association for Computational Linguistics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal","funders":"","keywords":"Information retrieval; Weighting; Computer science; Document Structure Description; Data mining; Medicine; XML; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001927905,0.00006574885,0.0001137792,0.00002041743,0.00008207496,0.00001522741,0.000095553,0.00007022386,0.000001187406],"category_scores_gemma":[0.003543131,0.0000523717,0.00006089644,0.00005518432,0.0001615165,0.000001864485,0.00005878281,0.0001074341,2.526832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001106524,"about_ca_system_score_gemma":0.0000567186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001130685,"about_ca_topic_score_gemma":0.00002823209,"domain_scores_codex":[0.9993544,0.00002097786,0.00027228,0.00009479764,0.0001705684,0.00008700479],"domain_scores_gemma":[0.9988269,0.0001197321,0.0004771131,0.00008821514,0.0004522342,0.00003585251],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001556641,0.00003137944,0.9717304,0.00002711116,0.0001744916,8.428127e-8,0.000111001,0.003273807,0.0009485829,0.004091118,0.0002650114,0.01919132],"study_design_scores_gemma":[0.001018534,0.0004261099,0.8537746,0.000009455826,0.00009880464,0.00000336081,0.00005514618,0.008628268,0.0009643257,0.003609486,0.1311687,0.0002431782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994579,0.000008949969,0.004229115,0.0001350832,0.0007077272,0.0001098164,0.0001639805,0.00000625866,0.00006008282],"genre_scores_gemma":[0.9687084,0.000004394179,0.03052942,0.000252378,0.0003785478,4.436484e-7,0.0001026299,0.000004390262,0.00001939223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1309037,"threshold_uncertainty_score":0.4241714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01164874062539717,"score_gpt":0.3002182539384063,"score_spread":0.2885695133130092,"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."}}