{"id":"W2047978531","doi":"10.1021/ac010486h","title":"Recovery of Gel-Separated Proteins for In-Solution Digestion and Mass Spectrometry","year":2001,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cancerfonden; Cancer Research Society","keywords":"Chemistry; Chromatography; Electroblotting; Sample preparation in mass spectrometry; Mass spectrometry; Protein mass spectrometry; Bottom-up proteomics; Tandem mass spectrometry; Matrix-assisted laser desorption/ionization; Trifluoroacetic acid; Electrospray ionization; Capillary electrophoresis–mass spectrometry; Sample preparation; Biochemistry; Polyacrylamide gel electrophoresis; Desorption; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007761167,0.0001103948,0.0001787428,0.00002725696,0.00003346947,0.0000109084,0.00008904747,0.0001657286,0.0001201961],"category_scores_gemma":[0.0001043547,0.0001178091,0.00005670472,0.0002024031,0.00007170792,0.00006014302,0.00002483048,0.0001541554,0.000001117255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009009615,"about_ca_system_score_gemma":0.00002546815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001367515,"about_ca_topic_score_gemma":0.000001424803,"domain_scores_codex":[0.9992052,0.000002447844,0.000264872,0.0002548525,0.00008211422,0.0001905676],"domain_scores_gemma":[0.9995219,0.00005990989,0.00009360915,0.0002091426,0.00005420679,0.00006126699],"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":[0.00009172336,0.00007784752,0.004827998,0.0001507871,0.00001265516,0.000001811026,0.000003370377,0.00002133176,0.9937807,0.0004938547,0.00004889892,0.0004890664],"study_design_scores_gemma":[0.0003588461,0.00002260588,0.0002293787,0.00006350744,0.00002348516,0.00001111109,0.00001260652,0.008048957,0.9773212,0.01251567,0.001236404,0.0001562203],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8981656,0.00009798587,0.08916332,0.0002647367,0.000003453851,0.00018658,0.00003580835,0.0000610773,0.01202146],"genre_scores_gemma":[0.971504,0.0001850853,0.02654265,0.00001115573,0.00005785011,0.0001353955,0.00007191564,0.00001496423,0.001477025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07333837,"threshold_uncertainty_score":0.4804117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01444934363029194,"score_gpt":0.2843973132380301,"score_spread":0.2699479696077381,"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."}}