{"id":"W4393022918","doi":"10.1101/2024.03.14.585104","title":"MetaDIA: A Novel Database Reduction Strategy for DIA Human Gut Metaproteomics","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Diet and metabolism studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metaproteomics; Reduction (mathematics); Database; Computer science; Computational biology; Chemistry; Biology; Metagenomics; Mathematics; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00231689,0.00172403,0.001544104,0.003656468,0.0009561217,0.002923289,0.002353987,0.0007346026,0.003944148],"category_scores_gemma":[0.004517796,0.0009111514,0.002013413,0.003017449,0.0004058432,0.002028245,0.003188437,0.001736402,0.002992621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006352727,"about_ca_system_score_gemma":0.002235217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001625816,"about_ca_topic_score_gemma":0.003158393,"domain_scores_codex":[0.9979963,0.0003145677,0.0002483547,0.0005418923,0.0007453479,0.0001535241],"domain_scores_gemma":[0.9982585,0.0004071525,0.0001789838,0.0004672979,0.0005550933,0.0001329527],"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":[0.001214584,0.0008096052,0.009731876,0.001108238,0.0007676198,0.0005769171,0.0004451239,0.01330213,0.3156404,0.007415725,0.02150207,0.6274857],"study_design_scores_gemma":[0.0002996701,0.0006738656,0.009061396,0.0001023054,0.0003585723,0.00170254,0.0005226654,0.570345,0.332642,0.01661235,0.06733228,0.0003473434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03249583,0.0007838669,0.9404525,0.0002695784,0.0001409222,0.0004304405,0.003314889,0.02072057,0.00139141],"genre_scores_gemma":[0.0449716,0.0002651351,0.9470425,0.0001899478,0.00004561508,0.0004430382,0.005405588,0.0007943725,0.0008421169],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003944148,"threshold_uncertainty_score":0.0131945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04837999400254996,"score_gpt":0.2916588616063667,"score_spread":0.2432788676038167,"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."}}