{"id":"W4403503812","doi":"10.1016/j.xpro.2024.103397","title":"Protocol for generating high-fidelity proteomic profiles using DROPPS","year":2024,"lang":"en","type":"article","venue":"STAR Protocols","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Terry Fox Research Institute; Canadian Cancer Society","keywords":"Protocol (science); Computer science; Computational biology; Fidelity; Biology; Medicine; Telecommunications","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":[0.002172452,0.002376773,0.001440208,0.001920493,0.002584236,0.001251379,0.002760775,0.001246432,0.03366515],"category_scores_gemma":[0.002312955,0.002113173,0.001047252,0.001599253,0.0009284376,0.001099152,0.002026761,0.004895045,0.03644605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000843934,"about_ca_system_score_gemma":0.002037802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00118565,"about_ca_topic_score_gemma":0.003173334,"domain_scores_codex":[0.9973787,0.0003996574,0.0003162271,0.0005834445,0.001093527,0.000228439],"domain_scores_gemma":[0.9980393,0.0004934213,0.0001230157,0.0005501405,0.0006023631,0.0001917609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000426172,0.0003063615,0.0004461408,0.001281767,0.0001003452,0.0006750512,0.000435469,0.0009432693,0.8878957,0.006265138,0.06601421,0.03521045],"study_design_scores_gemma":[0.000216566,0.0003444435,0.001285915,0.0001677973,0.00008226772,0.001007203,0.00006973146,0.00459153,0.5661544,0.002736285,0.4231498,0.0001941698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"protocol","genre_scores_codex":[0.0176655,0.002315111,0.9023625,0.001019993,0.001496978,0.01195867,0.02294365,0.01947306,0.02076457],"genre_scores_gemma":[0.04715649,0.005150917,0.7860175,0.001889432,0.0003382873,0.04240613,0.07266284,0.005048404,0.03932996],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.03366515,"threshold_uncertainty_score":0.1126211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06602641676116533,"score_gpt":0.4091775387148643,"score_spread":0.343151121953699,"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."}}