{"id":"W7101030672","doi":"","title":"Statistical Analysis of High-Throughput Genetic Data Jiahua Chen (University of British Columbia),","year":2007,"lang":"en","type":"article","venue":"","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Human genetics; Genomics; Human genome; DNA microarray; Genome; Chen; DECIPHER; Single-nucleotide polymorphism; Milestone; Human genetic variation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009383704,0.000685556,0.001734964,0.003844972,0.001279988,0.002412949,0.001081338,0.000517629,0.003281473],"category_scores_gemma":[0.06159218,0.0004897721,0.001220579,0.006124316,0.001379374,0.0005806681,0.001072564,0.002259192,0.0008988082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002362072,"about_ca_system_score_gemma":0.006492725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06693053,"about_ca_topic_score_gemma":0.07615824,"domain_scores_codex":[0.9927675,0.002931289,0.0004139713,0.001436551,0.002235121,0.0002156055],"domain_scores_gemma":[0.943017,0.0429274,0.002123206,0.004524873,0.006100234,0.0013072],"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":[0.001243431,0.0001726225,0.1594662,0.001609537,0.004181543,0.001286415,0.0004553597,0.0238951,0.01054373,0.009774301,0.08133548,0.7060364],"study_design_scores_gemma":[0.0003779492,0.0004854072,0.3330815,0.0007292749,0.001497743,0.00150226,0.0005857298,0.4497299,0.01573592,0.06899732,0.126932,0.0003448989],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1094982,0.02963574,0.8038104,0.01329621,0.002444656,0.0008035867,0.02827141,0.008010737,0.004229162],"genre_scores_gemma":[0.5757768,0.01267956,0.365064,0.00182845,0.001180731,0.001675413,0.026056,0.001554681,0.01418434],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06693053,"threshold_uncertainty_score":0.1330819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531727002579626,"score_gpt":0.253265392735339,"score_spread":0.2379481227095428,"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."}}