{"id":"W4301179742","doi":"10.32920/ryerson.14669061.v2","title":"Creation of a federated database of blood proteins: a powerful new tool for finding and characterizing biomarkers in serum","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Fonds National de la Recherche Luxembourg","keywords":"Computer science; Database; SQL; Computational biology; Proteomics; Bioinformatics; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005508859,0.0009860886,0.002076636,0.01090462,0.0007338546,0.003800771,0.001659099,0.0009249755,0.002473931],"category_scores_gemma":[0.008306959,0.0005403844,0.001271582,0.00828125,0.0004809533,0.00342505,0.002123422,0.0009705898,0.002194493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007333593,"about_ca_system_score_gemma":0.002282562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009060152,"about_ca_topic_score_gemma":0.0007257841,"domain_scores_codex":[0.9971529,0.0005649896,0.000626844,0.0005779061,0.0009768171,0.0001005169],"domain_scores_gemma":[0.9950231,0.001340191,0.0008111295,0.001276741,0.001175315,0.0003735226],"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":[0.001834487,0.0005369317,0.02275201,0.008275342,0.001111616,0.002360664,0.001037693,0.007307415,0.1024394,0.01761221,0.03319456,0.8015377],"study_design_scores_gemma":[0.0003477018,0.0009610977,0.04389332,0.002563753,0.001467044,0.008945568,0.0008203334,0.0531903,0.191081,0.06761403,0.6285701,0.0005457656],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.09421155,0.03906773,0.729305,0.002773049,0.0006672931,0.0008259942,0.08703444,0.03671001,0.00940495],"genre_scores_gemma":[0.1518532,0.01620964,0.7080814,0.0009218987,0.0002761358,0.0005871354,0.1173334,0.001166497,0.003570632],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01090462,"threshold_uncertainty_score":0.02913398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308026303885203,"score_gpt":0.3048221189938589,"score_spread":0.2817418559550068,"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."}}