{"id":"W2365672368","doi":"","title":"An Investigation of the Eectiveness of Concept-based Approach in Medical Information Retrieval GRIUM @ CLEF2014eHealthTask 3","year":2014,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Clef; Computer science; Information retrieval; Task (project management); Unified Medical Language System; Natural language processing; Artificial intelligence; Resource (disambiguation); Domain (mathematical analysis)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04413652,0.002004265,0.001423274,0.007551047,0.001101779,0.0035745,0.002527385,0.002969346,0.002778428],"category_scores_gemma":[0.09472799,0.0005999079,0.001163857,0.004603745,0.001394045,0.006313072,0.003511018,0.002102182,0.001031423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001776606,"about_ca_system_score_gemma":0.001417013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00709311,"about_ca_topic_score_gemma":0.004597064,"domain_scores_codex":[0.9666577,0.02207341,0.002339287,0.002025741,0.006276726,0.0006271771],"domain_scores_gemma":[0.8105449,0.1745165,0.0029194,0.004104927,0.006764886,0.001149407],"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":[0.006801141,0.004428794,0.03117612,0.005983233,0.001663541,0.0004550271,0.002955934,0.02277922,0.02672877,0.004858156,0.01104088,0.8811293],"study_design_scores_gemma":[0.002469958,0.01491823,0.0902259,0.0009193849,0.001629416,0.002021122,0.004825125,0.7767984,0.06843419,0.0124888,0.02463036,0.000639163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7532152,0.0283579,0.1761399,0.004401708,0.000842455,0.003107715,0.002937617,0.004668392,0.02632921],"genre_scores_gemma":[0.7016866,0.004081971,0.2853228,0.0008510703,0.0003516837,0.0008048363,0.002395174,0.0003232915,0.004182554],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04413652,"threshold_uncertainty_score":0.2334189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01115093977129494,"score_gpt":0.2625488301593654,"score_spread":0.2513978903880704,"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."}}