{"id":"W2046399369","doi":"10.1016/j.aca.2013.08.005","title":"Maximizing recovery of water-soluble proteins through acetone precipitation","year":2013,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":166,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Acetone; Chemistry; Precipitation; Protein precipitation; Solvent; Proteome; Yield (engineering); Chromatography; Salt (chemistry); Ionic strength; Biochemistry; Aqueous solution; Mass spectrometry; Organic chemistry","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":[0.001227919,0.00198502,0.0008039702,0.00075812,0.0006652565,0.000859075,0.0009143963,0.0007285762,0.00114334],"category_scores_gemma":[0.001122612,0.0005299023,0.0005942913,0.0009245225,0.000565784,0.0008366976,0.0007327268,0.001018862,0.00146923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000468812,"about_ca_system_score_gemma":0.0008421704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001525098,"about_ca_topic_score_gemma":0.003220146,"domain_scores_codex":[0.9986808,0.0002169903,0.00009554155,0.000322741,0.0004349907,0.0002488611],"domain_scores_gemma":[0.9996148,0.00009954118,0.00006719952,0.00007400609,0.0001243976,0.00001991969],"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":[0.00003813447,0.00002306552,0.0001276592,0.0000617393,0.000008380237,0.00004508427,0.00002188478,0.0001001878,0.9964871,0.0000870946,0.000107702,0.002891878],"study_design_scores_gemma":[0.000002781902,0.00002868356,0.0002432719,0.000004166535,0.000008395028,0.00004538002,0.000006314554,0.0002825665,0.9978719,0.00004379138,0.001459845,0.000002927523],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6709706,0.008805295,0.3031549,0.001011492,0.0004377969,0.001172883,0.001337168,0.002081079,0.01102887],"genre_scores_gemma":[0.7102787,0.01137716,0.2577528,0.0006119838,0.0001275487,0.0005389683,0.002660798,0.0008600681,0.01579194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00198502,"threshold_uncertainty_score":0.006493926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535010854597211,"score_gpt":0.2505701580370037,"score_spread":0.2352200494910316,"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."}}