{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004551909,0.0009650214,0.001638743,0.004971077,0.001191112,0.003458126,0.0021336,0.001987489,0.002626638],"category_scores_gemma":[0.02597743,0.0004323827,0.0009934343,0.009039749,0.003185571,0.007715606,0.00336719,0.00232284,0.001250727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002219914,"about_ca_system_score_gemma":0.001608899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001910618,"about_ca_topic_score_gemma":0.0008733585,"domain_scores_codex":[0.9912076,0.002744874,0.0009599359,0.001320419,0.003560691,0.0002064979],"domain_scores_gemma":[0.9923347,0.003342119,0.0006557382,0.0009525725,0.002452191,0.0002627711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005251676,0.00003041136,0.0006283824,0.0002793786,0.00005220859,0.0002034986,0.000215136,0.02207495,0.002867129,0.7549027,0.005826168,0.2128677],"study_design_scores_gemma":[0.00001168227,0.00007457186,0.0003789189,0.0001149638,0.00002817284,0.0008133755,0.0001013556,0.1472784,0.003259387,0.7975348,0.05033362,0.00007080753],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003560383,0.004652842,0.9818823,0.0005987275,0.0003775147,0.00006907238,0.0001312453,0.000291733,0.008436187],"genre_scores_gemma":[0.1730321,0.008411163,0.8099568,0.0005683362,0.0009715156,0.0004195751,0.0006564526,0.0003497139,0.00563432],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004971077,"threshold_uncertainty_score":0.02407306,"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."}}