{"id":"W3008294444","doi":"10.2196/16777","title":"Translating Clinical Questions by Physicians Into Searchable Queries: Analytical Survey Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Education","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Computer science; Information retrieval; Context (archaeology); Service (business); MEDLINE; Search engine; World Wide Web; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03481923,0.0004307679,0.001293927,0.006270909,0.001117646,0.002766019,0.001009797,0.001360285,0.00303227],"category_scores_gemma":[0.2103897,0.0007767621,0.001126939,0.008852278,0.001678303,0.004101372,0.002576728,0.001236762,0.001732842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003269228,"about_ca_system_score_gemma":0.005557269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006499951,"about_ca_topic_score_gemma":0.00610774,"domain_scores_codex":[0.9483073,0.02544328,0.01391926,0.004454913,0.005814254,0.002060999],"domain_scores_gemma":[0.7219966,0.2005517,0.04739302,0.006053721,0.02026699,0.003737864],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001545246,0.001408812,0.8952802,0.004220152,0.0004838559,0.0004320339,0.04290023,0.0003454406,0.0006304469,0.000574716,0.005812142,0.04636677],"study_design_scores_gemma":[0.0009203627,0.004219545,0.889527,0.002850346,0.0007142554,0.002186776,0.06974929,0.004840371,0.001256508,0.0009376393,0.02258638,0.0002113853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896327,0.001613719,0.001476375,0.0006875084,0.00001738227,0.001804407,0.003218439,0.00005489246,0.001494528],"genre_scores_gemma":[0.9875633,0.001403352,0.003958449,0.001464281,0.00004184381,0.003160441,0.002043384,0.00004185371,0.0003232945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9651808,"threshold_uncertainty_score":0.1841439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04694446460236983,"score_gpt":0.4342116643875008,"score_spread":0.3872671997851309,"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."}}