{"id":"W2020302515","doi":"10.1371/journal.pcbi.0030106","title":"A Survey of Genomic Properties for the Detection of Regulatory Polymorphisms","year":2007,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; BC Cancer Foundation; Genome British Columbia; Wellcome Trust; Canadian Institutes of Health Research; Genome Canada; Michael Smith Health Research BC; European Molecular Biology Organization","keywords":"Genetics; Biology; Computational biology; Gene; Regulatory sequence; Single-nucleotide polymorphism; Allele; CpG site; DNA binding site; Locus (genetics); Genomics; Genome; Transcription factor; Promoter; Genotype; Gene expression; DNA methylation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005211144,0.00006645794,0.000105326,0.00004046068,0.00004677754,0.000001946147,0.0001262568,0.00008449407,0.000003266722],"category_scores_gemma":[0.0002568672,0.00004705417,0.0000452564,0.00004529638,0.0001701066,0.000001376114,0.00004760039,0.00004189823,0.00000122095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007236955,"about_ca_system_score_gemma":0.00005418936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005052512,"about_ca_topic_score_gemma":0.00004229397,"domain_scores_codex":[0.9994147,0.00005368784,0.000280899,0.00009356629,0.00005642671,0.0001006534],"domain_scores_gemma":[0.999243,0.0001971591,0.0001979854,0.0001212619,0.0002256009,0.00001497674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002598735,0.00003536497,0.01444475,0.00003521821,0.0001099323,2.046596e-8,0.00006204768,0.005175569,0.9747816,0.0003205112,0.00002188092,0.004753178],"study_design_scores_gemma":[0.0005030874,0.0006419703,0.6262088,0.000008361367,0.00002401041,0.000006731032,0.00002968432,0.03781413,0.3336055,0.000293655,0.000742324,0.0001216583],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8641393,0.0006027223,0.1348608,0.00003236108,0.00007464818,0.0001950547,0.0000458816,0.000004574439,0.00004477133],"genre_scores_gemma":[0.99709,0.000006690364,0.002575287,0.00006597191,0.00004975608,0.000007589081,0.0001714441,0.000007681203,0.00002562024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6411761,"threshold_uncertainty_score":0.1918813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02433733132852697,"score_gpt":0.2571879161148566,"score_spread":0.2328505847863297,"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."}}