{"id":"W4399993467","doi":"10.1101/2024.06.20.599973","title":"LooMS: a novel peptide identification tools for data independent acquisition","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto; University of Waterloo","funders":"","keywords":"Identification (biology); Computer science; Computational biology; Biology","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":[0.003471845,0.00149071,0.0009078835,0.002841079,0.0005218559,0.001400415,0.001977166,0.001048539,0.005795728],"category_scores_gemma":[0.008053546,0.0006503208,0.001290566,0.001236479,0.0005791076,0.002463935,0.003209304,0.001367393,0.002110287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003481265,"about_ca_system_score_gemma":0.001234591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004711479,"about_ca_topic_score_gemma":0.001073181,"domain_scores_codex":[0.9986252,0.0002245698,0.0001413319,0.0003576735,0.0005430991,0.0001082466],"domain_scores_gemma":[0.9967519,0.001695555,0.0004919363,0.0004428979,0.0004409129,0.0001767856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004407376,0.0004946811,0.01438765,0.002078383,0.0008834301,0.002039685,0.0004519747,0.02707174,0.2212146,0.0117151,0.05667273,0.6585825],"study_design_scores_gemma":[0.00044358,0.000579066,0.007469818,0.0001598939,0.0001746895,0.001422298,0.0001548492,0.7558084,0.1670698,0.02644226,0.04001355,0.0002618894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03396079,0.0008753913,0.8887543,0.0003396304,0.0001422512,0.0002656773,0.004199164,0.07000648,0.001456348],"genre_scores_gemma":[0.1355173,0.0003442462,0.8488205,0.0008881459,0.0001065328,0.0008441841,0.008521531,0.002865311,0.002092298],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005795728,"threshold_uncertainty_score":0.01938862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.037640303137876,"score_gpt":0.2846991337125002,"score_spread":0.2470588305746242,"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."}}