{"id":"W2080867027","doi":"10.1186/1471-2105-12-s9-s9","title":"Detecting genomic regions associated with a disease using variability functions and Adjusted Rand Index","year":2011,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational biology; Biology; Identification (biology); Functional genomics; DNA microarray; Genetics; Function (biology); Genomics; Bioinformatics; Genome; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00500901,0.001090883,0.001057794,0.003734811,0.0006343421,0.001213779,0.001199268,0.001472234,0.001501294],"category_scores_gemma":[0.01382914,0.0002750845,0.001538936,0.001534366,0.0009875849,0.001094044,0.001000369,0.001095281,0.0003634274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009587352,"about_ca_system_score_gemma":0.0007684939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002388717,"about_ca_topic_score_gemma":0.001510224,"domain_scores_codex":[0.9981597,0.0006443106,0.000151103,0.0005694766,0.0003560132,0.0001193386],"domain_scores_gemma":[0.986419,0.00984245,0.001834127,0.0007459064,0.0008322437,0.0003262123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001002157,0.000251874,0.08059192,0.000293843,0.0003960083,0.0002887365,0.0002316203,0.642626,0.01298085,0.00587199,0.001943993,0.2535211],"study_design_scores_gemma":[0.00002543351,0.0001680895,0.009651096,0.00002297902,0.00004963662,0.0001961084,0.00003004312,0.9800134,0.003878011,0.005429823,0.0004927776,0.00004250969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2537519,0.0008671032,0.7418501,0.0003055786,0.00003299851,0.0001327525,0.0004672172,0.001363803,0.001228529],"genre_scores_gemma":[0.6309552,0.0001765554,0.3668072,0.0001023596,0.00004247464,0.0001954379,0.0009515337,0.0001873908,0.0005819422],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00500901,"threshold_uncertainty_score":0.02649051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03697424106330998,"score_gpt":0.2178551642141747,"score_spread":0.1808809231508647,"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."}}