{"id":"W2067040469","doi":"10.1016/j.ygeno.2009.02.007","title":"Optimizing comparative genomic hybridization probes for genotyping and SNP detection in Plasmodium falciparum","year":2009,"lang":"en","type":"article","venue":"Genomics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"National Institutes of Health; Broad Institute; Wellcome Trust; National Institute of Allergy and Infectious Diseases; University of Notre Dame","keywords":"Biology; Genotyping; Molecular Inversion Probe; Genetics; SNP genotyping; SNP array; Single-nucleotide polymorphism; DNA microarray; Comparative genomic hybridization; Tandem repeat; SNP; Copy-number variation; High Resolution Melt; Genome; Computational biology; Genotype; Gene","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":[0.0001345058,0.0001482983,0.0001720802,0.0000586023,0.0001391539,0.00003239407,0.00008296246,0.00008136419,4.340861e-7],"category_scores_gemma":[0.00001488559,0.0001647623,0.0000414974,0.00004585468,0.00003480929,0.000001752175,0.00005391703,0.00004811274,9.9775e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003753691,"about_ca_system_score_gemma":0.00004427435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000855437,"about_ca_topic_score_gemma":0.0001052054,"domain_scores_codex":[0.9991768,0.00002157615,0.0002135942,0.0003223437,0.00003215672,0.0002335394],"domain_scores_gemma":[0.9996896,0.00001145307,0.0000779061,0.0001296377,0.00005158111,0.00003985659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000126421,0.00002137846,0.0003306507,0.000009569766,0.00002521435,2.513082e-7,0.0006441029,0.00931512,0.9845096,0.00008529753,0.00002314055,0.00490918],"study_design_scores_gemma":[0.001574544,0.0007188078,0.03023532,0.00001255424,0.00003763157,0.00001547623,0.0005438732,0.01324769,0.9379448,0.001304327,0.01386663,0.0004983211],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813001,0.002428866,0.01543655,0.0000861127,0.0001009337,0.0004812503,0.00002000895,0.000004420498,0.0001417358],"genre_scores_gemma":[0.9916438,0.0006080575,0.007335386,0.0001490874,0.0001454364,0.00003484591,0.00003716944,0.00001409486,0.00003213241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04656485,"threshold_uncertainty_score":0.6718813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03057838385720449,"score_gpt":0.2686762755274831,"score_spread":0.2380978916702786,"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."}}