{"id":"W4391096444","doi":"10.1109/bigdata59044.2023.10386854","title":"Integrating a PICO Clinical Questioning to the QL4POMR Framework for Building Evidence-Based Clinical Case Reports","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Harmonization; Flexibility (engineering); Clinical Practice; MEDLINE; Data science; Medical education; Medicine; Family medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01126743,0.0001742039,0.0003220109,0.0001130624,0.0004552328,0.0004449815,0.0006671108,0.0001955357,0.000009206063],"category_scores_gemma":[0.02907395,0.0001197896,0.00029259,0.0008088314,0.00005058241,0.0003677867,0.0005023542,0.000601556,0.00003497628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004745283,"about_ca_system_score_gemma":0.0002805711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000132068,"about_ca_topic_score_gemma":0.00007828147,"domain_scores_codex":[0.9963803,0.000397954,0.001461967,0.0009511524,0.000344933,0.0004636652],"domain_scores_gemma":[0.9863062,0.01151903,0.0002989061,0.001412492,0.0002287516,0.0002346199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003184477,0.00008688679,0.03578066,0.00004784204,0.00004832938,0.004128487,0.0007678575,0.02319479,0.00002736567,0.3887835,0.007012459,0.54009],"study_design_scores_gemma":[0.0001250953,0.00019433,0.0007905533,0.0006658228,0.00001493981,0.0004995958,0.0001398989,0.9717931,0.0000655769,0.02261944,0.002871087,0.0002206163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1076405,0.00004773707,0.874204,0.0143045,0.002603724,0.0005360519,4.721313e-7,0.0006090791,0.00005393443],"genre_scores_gemma":[0.4543274,0.0000049208,0.5417226,0.003097051,0.0006636378,0.00008174962,4.405911e-7,0.00001092686,0.00009131516],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9485983,"threshold_uncertainty_score":0.9791046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2519922526369645,"score_gpt":0.4781043201092977,"score_spread":0.2261120674723332,"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."}}