{"id":"W4390331298","doi":"10.1371/journal.pgen.1011104","title":"SparsePro: An efficient fine-mapping method integrating summary statistics and functional annotations","year":2023,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Fonds de recherche du Québec; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Compute Canada","keywords":"Biology; Computational biology; Statistics; Mathematics","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":[0.0002433015,0.000112781,0.0001083239,0.0001277251,0.0002595357,0.0001695883,0.000236063,0.00003973362,0.000008834819],"category_scores_gemma":[0.00008086953,0.0001034529,0.00001539874,0.0004279823,0.0000292241,0.0001193866,0.0003736044,0.0001193979,0.00002449015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001463108,"about_ca_system_score_gemma":0.00006089496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006068558,"about_ca_topic_score_gemma":0.00000967572,"domain_scores_codex":[0.9988693,0.00007941722,0.0002019653,0.0003562099,0.0002830258,0.0002101099],"domain_scores_gemma":[0.9991037,0.0002468363,0.00006551587,0.000353546,0.0001246624,0.0001058004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001532708,0.000569178,0.004352652,0.0001903695,0.0001302962,0.0001025986,0.007697469,0.1982359,0.04995231,0.07282417,0.03414562,0.6317841],"study_design_scores_gemma":[0.0001198236,0.00004817531,0.0038425,0.0000276509,0.000007260597,0.000005746721,0.0001144277,0.9905474,0.001181009,0.002173351,0.00180219,0.0001305254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02712942,0.0001249447,0.9718478,0.0001588859,0.0002418624,0.000112306,0.0001036893,0.0001686117,0.0001125352],"genre_scores_gemma":[0.01817279,0.00002859408,0.9812373,0.00009772159,0.0001245306,0.00001854539,0.0002009246,0.00001281695,0.0001067746],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7923114,"threshold_uncertainty_score":0.4218687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06113417445881297,"score_gpt":0.2973552104861238,"score_spread":0.2362210360273109,"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."}}