{"id":"W4318753623","doi":"10.1021/acs.analchem.2c04264","title":"ASAP─Automated Sonication-Free Acid-Assisted Proteomes─from Cells and FFPE Tissues","year":2023,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Michael Cuccione Foundation; University of British Columbia; Mitacs; Canada Research Chairs; BC Children's Hospital; Michael Smith Health Research BC; BC Children’s Hospital Foundation; Children's Hospital Foundation","keywords":"Proteome; Workflow; Chemistry; Sample preparation; Sonication; Proteomics; Pipeline (software); Computational biology; Chromatography; Computer science; Database; Biochemistry; Biology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008037852,0.0002343136,0.0002660224,0.00002393093,0.0001444544,0.00007530747,0.0004638231,0.0002774965,0.001187209],"category_scores_gemma":[0.0001488405,0.0002385626,0.00008085124,0.0003351934,0.0001660745,0.0000703502,0.0003051115,0.0002977772,0.0001573007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006659725,"about_ca_system_score_gemma":0.00004860411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000468133,"about_ca_topic_score_gemma":0.000001500242,"domain_scores_codex":[0.9985089,0.000006047395,0.0003503154,0.0005609097,0.0002252289,0.000348608],"domain_scores_gemma":[0.9985222,0.0001098297,0.000118514,0.0009593409,0.00007829418,0.0002118221],"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":[0.00001003535,0.00005758766,0.0005588196,0.0001226295,0.00005431958,0.00001323193,0.00002618273,0.000006412811,0.9886032,0.0002657929,0.009067359,0.001214407],"study_design_scores_gemma":[0.0003144217,0.000004894679,0.0002763982,0.00005434069,0.00005532829,0.000005244277,0.00006401495,0.01366273,0.966415,0.006148916,0.01269463,0.0003040876],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631777,0.0002422699,0.001302072,0.002666373,0.0000157697,0.0003062739,0.0004332366,0.004577685,0.02727863],"genre_scores_gemma":[0.9736242,0.0002543699,0.01593499,0.00009303878,0.0002129989,0.0003599874,0.0005111594,0.00007242336,0.008936874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02218822,"threshold_uncertainty_score":0.9997258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670598663194153,"score_gpt":0.2964341212854215,"score_spread":0.27972813465348,"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."}}