{"id":"W2773351420","doi":"10.2196/medinform.7059","title":"Search and Graph Database Technologies for Biomedical Semantic Indexing: Experimental Analysis","year":2017,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Search engine indexing; Information retrieval; Graph database; Graph; Database; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01234961,0.002286184,0.001478474,0.007420927,0.001279978,0.001813727,0.00189939,0.001675151,0.004349951],"category_scores_gemma":[0.03131985,0.0004644503,0.002095149,0.006549304,0.001171327,0.004717303,0.00254228,0.001237267,0.001766694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002576267,"about_ca_system_score_gemma":0.001982823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01337889,"about_ca_topic_score_gemma":0.01076873,"domain_scores_codex":[0.9866326,0.006603463,0.001494354,0.001395868,0.003211573,0.0006621464],"domain_scores_gemma":[0.9632551,0.02709834,0.001629371,0.003350779,0.004146264,0.0005201812],"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":[0.01432518,0.01966274,0.03437029,0.01077746,0.00318525,0.0005087592,0.001005749,0.05144273,0.02672383,0.004722338,0.04187671,0.7913989],"study_design_scores_gemma":[0.004505029,0.02356352,0.08996789,0.001183176,0.005274294,0.001790442,0.004157644,0.7171909,0.09918338,0.01822933,0.0344024,0.0005519512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8567081,0.02316878,0.06986393,0.001439645,0.0009778708,0.005072718,0.01893114,0.008306417,0.01553133],"genre_scores_gemma":[0.78837,0.006354039,0.1561874,0.000476876,0.0003162584,0.002871241,0.04111136,0.0005684426,0.003744376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01337889,"threshold_uncertainty_score":0.06531179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03028209886436811,"score_gpt":0.3609085883083696,"score_spread":0.3306264894440015,"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."}}