{"id":"W1981208872","doi":"10.1002/pmic.201400188","title":"Whole cell, label free protein quantitation with data independent acquisition: Quantitation at the MS2 level","year":2014,"lang":"en","type":"article","venue":"PROTEOMICS","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Manitoba; Research Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Label-free quantification; Quantitative proteomics; Replicate; Peptide; Chromatography; Chemistry; Mass spectrometry; Quantitative analysis (chemistry); Computational biology; Proteomics; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004169171,0.000225973,0.0001690784,0.00003586174,0.0004648982,0.0001122857,0.001026389,0.0001499344,0.0001271764],"category_scores_gemma":[0.00008415359,0.0001740274,0.00003148588,0.0001658282,0.0001212647,0.0003545536,0.0005166783,0.0003125976,0.000105615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001262024,"about_ca_system_score_gemma":0.00006425547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007583384,"about_ca_topic_score_gemma":0.0001772973,"domain_scores_codex":[0.9984584,0.00003774611,0.0003268383,0.0005563081,0.0003482337,0.0002725158],"domain_scores_gemma":[0.9973954,0.00007142739,0.0003433873,0.001966071,0.0001552923,0.00006844586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001399431,0.0001465068,0.0003755451,0.0001461006,0.00001997293,9.591694e-7,0.0001324658,0.0002088152,0.9786536,0.01707373,0.001468976,0.001633371],"study_design_scores_gemma":[0.001494257,0.0001165746,0.000187496,0.0001156354,0.00004551161,0.0000142268,0.0001732961,0.01425955,0.9444723,0.02339297,0.0152489,0.0004793115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3713423,0.00008205853,0.6216328,0.002211281,0.00001992911,0.001272896,0.0005329117,0.0002085878,0.002697212],"genre_scores_gemma":[0.4953608,0.00002492835,0.4985077,0.0001882466,0.0001822195,0.001428154,0.001326735,0.00007538097,0.002905844],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1240185,"threshold_uncertainty_score":0.709663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0501460282801692,"score_gpt":0.2926556869588405,"score_spread":0.2425096586786713,"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."}}