{"id":"W2115866389","doi":"10.1109/bibm.2007.12","title":"The Normalized Similarity Metric and Its Applications","year":2007,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Similarity (geometry); Metric (unit); Computer science; Metric space; Mathematics; Domain (mathematical analysis); Formal description; Theoretical computer science; Data mining; Artificial intelligence; Discrete mathematics","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":[0.0004656282,0.00005788651,0.00004029004,0.00002155257,0.0001817476,0.00002395585,0.0001155537,0.00006031106,0.000009722413],"category_scores_gemma":[0.0001753048,0.00003821258,0.00002102358,0.0001074066,0.00003244432,0.000001541934,0.00009053853,0.00006827941,0.00001201882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003243165,"about_ca_system_score_gemma":0.00001103902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004110103,"about_ca_topic_score_gemma":0.00003294136,"domain_scores_codex":[0.9995716,0.00001268632,0.000129069,0.00008184135,0.00006859352,0.0001361785],"domain_scores_gemma":[0.9996325,0.00005565638,0.00004184697,0.0001743313,0.00004804133,0.00004762243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004152453,0.0002904123,0.0728269,0.000257895,0.0004506699,0.000003393832,0.0003834332,0.0002992632,0.2976671,0.2242571,0.02629006,0.3768586],"study_design_scores_gemma":[0.0002690931,0.00005511949,0.009604273,8.306498e-7,0.000009859233,0.00001482616,0.00005908109,0.001482697,0.04972058,0.0000907448,0.9385768,0.0001160504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3321878,0.005494182,0.3542147,0.001555322,0.0001708754,0.001178099,0.0000133937,0.0001041488,0.3050814],"genre_scores_gemma":[0.9914082,0.0003627918,0.004041179,0.000470327,0.00008252906,0.00001336314,0.00002369544,0.000006886284,0.003591075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9122868,"threshold_uncertainty_score":0.1558264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005663656752220411,"score_gpt":0.2732706083868433,"score_spread":0.2676069516346229,"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."}}