{"id":"W1991348882","doi":"10.1016/j.chroma.2015.03.034","title":"Thermo-responsive adsorbent for size-selective protein adsorption","year":2015,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Protein purification and stability","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"University of Waterloo; Universiti Putra Malaysia; Canadian Bureau for International Education; Commonwealth Fund","keywords":"Chemistry; Adsorption; Methacrylate; Protein adsorption; Chromatography; Lower critical solution temperature; Agarose; Bovine serum albumin; Ethylene glycol; Polymer chemistry; Copolymer; Desorption; Polymer; 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":[0.0002592853,0.0004589177,0.0003009005,0.0004418269,0.0003270697,0.0003227299,0.0005086208,0.0006568988,0.001243372],"category_scores_gemma":[0.0002336154,0.0003033506,0.0003903031,0.0002673694,0.0002258124,0.0003410687,0.0003823368,0.0007461812,0.0008021727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000331218,"about_ca_system_score_gemma":0.0002313456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003518125,"about_ca_topic_score_gemma":0.000779875,"domain_scores_codex":[0.9997469,0.00003009879,0.00001535208,0.00004641952,0.0001042883,0.0000569355],"domain_scores_gemma":[0.9998767,0.00002618048,0.00002104174,0.00001362398,0.00003767505,0.00002471448],"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":[0.00002474944,0.00001591319,0.00003075596,0.0000230914,0.000003382916,0.00001714574,0.000009144071,0.00004396129,0.9984379,0.0001038983,0.0001155375,0.001174562],"study_design_scores_gemma":[0.000002477745,0.00004262312,0.0004411644,0.000002309312,0.00000625504,0.00005056777,0.000005553806,0.001050991,0.9972245,0.00002534379,0.001140621,0.000007565814],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9472855,0.003261582,0.04244916,0.0003776248,0.0002970636,0.000104986,0.0004247789,0.0008709146,0.004928236],"genre_scores_gemma":[0.9771914,0.001119314,0.01340074,0.0002414184,0.00005743899,0.00008073481,0.000507306,0.00009120828,0.007310418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001243372,"threshold_uncertainty_score":0.00415951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764960181494232,"score_gpt":0.273164280612781,"score_spread":0.2555146787978387,"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."}}