{"id":"W2056992525","doi":"10.1021/ac060790g","title":"Non-Size-Based Membrane Chromatographic Separation and Analysis of Monoclonal Antibody Aggregates","year":2006,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Chemistry; Monoclonal antibody; Chromatography; Size-exclusion chromatography; Resolution (logic); Antibody; Membrane; Monomer; Aggregate (composite); Polymer; Biochemistry; Nanotechnology; Enzyme; 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":[0.0005814302,0.0004213843,0.0003368019,0.0006297403,0.0003765483,0.0003796226,0.0005753697,0.0006611705,0.001225522],"category_scores_gemma":[0.0007034768,0.000221916,0.0003453353,0.0003387058,0.0003235555,0.0004945919,0.0003675873,0.0007739621,0.001017843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000373907,"about_ca_system_score_gemma":0.0003606717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004313425,"about_ca_topic_score_gemma":0.0007968871,"domain_scores_codex":[0.9993545,0.0001462503,0.00004287051,0.00008129808,0.0003168237,0.00005825136],"domain_scores_gemma":[0.9994386,0.0002049602,0.00009828088,0.00006871129,0.0001396459,0.00004974234],"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":[0.00001665848,0.00001495004,0.00007933505,0.00002955913,0.000003672017,0.00002358552,0.00001251403,0.00002214675,0.9971614,0.0001211753,0.00004563931,0.002469328],"study_design_scores_gemma":[0.000006066925,0.00009213736,0.001959805,0.000004405296,0.000008674713,0.0002993238,0.00001454797,0.001007457,0.9945766,0.0001202626,0.001904237,0.000006636724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5680864,0.007902284,0.4139498,0.0005462269,0.0001769335,0.0003991166,0.0005508477,0.0008032626,0.007585028],"genre_scores_gemma":[0.7066396,0.007198872,0.2704591,0.0003978388,0.0001128921,0.0006530357,0.00114599,0.0001996375,0.01319303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001225522,"threshold_uncertainty_score":0.004099786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01011406958063643,"score_gpt":0.3198005291147179,"score_spread":0.3096864595340815,"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."}}