{"id":"W4399274414","doi":"10.1101/2024.05.27.596028","title":"A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cytodiagnostics (Canada)","funders":"Weill Cornell Medicine - Qatar; Weill Cornell Medical College","keywords":"Proteomics; Computational biology; Mass spectrometry; Genome-wide association study; Computer science; Biology; Chromatography; Chemistry; Genetics; Single-nucleotide polymorphism; Gene; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001305586,0.0005462168,0.0004793614,0.001242441,0.0003631186,0.0007833246,0.0003359495,0.0004348375,0.007518213],"category_scores_gemma":[0.002175593,0.0001775915,0.0009869298,0.001614921,0.0001795989,0.0002060088,0.0004076987,0.0005645078,0.0005997028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002498845,"about_ca_system_score_gemma":0.00032139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001847065,"about_ca_topic_score_gemma":0.003352893,"domain_scores_codex":[0.9992039,0.0002534405,0.0000538128,0.000278674,0.0001419976,0.00006817395],"domain_scores_gemma":[0.9987049,0.0005498742,0.0003820734,0.0001417327,0.0001473877,0.00007400885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005282365,0.0002008116,0.8719163,0.001484302,0.01022232,0.001760224,0.0001834333,0.00223218,0.03347577,0.002019149,0.01589937,0.05532386],"study_design_scores_gemma":[0.0002644811,0.0006618946,0.9654019,0.0001441504,0.004703696,0.001344726,0.0001374684,0.005801516,0.009645519,0.002063165,0.009774307,0.00005728846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9455857,0.003976232,0.01073773,0.001322704,0.0001981115,0.0001390622,0.03457451,0.0005369533,0.002928904],"genre_scores_gemma":[0.9849296,0.00063085,0.007962001,0.000238917,0.00006884905,0.0000708996,0.004856254,0.0000524821,0.001190095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007518213,"threshold_uncertainty_score":0.0251509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01572344142518591,"score_gpt":0.2465974678766401,"score_spread":0.2308740264514542,"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."}}