{"id":"W2522213059","doi":"10.1016/j.chroma.2016.09.044","title":"Using a box instead of a column for process chromatography","year":2016,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Protein purification and stability","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Chromatography; Chemistry; Elution; Column chromatography; Countercurrent chromatography; Chromatography column; Two-dimensional chromatography; Resolution (logic); Packed bed; High-performance liquid chromatography; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002329461,0.001739127,0.00199661,0.001208818,0.0009732451,0.002435866,0.001981107,0.002895591,0.01837825],"category_scores_gemma":[0.002413224,0.001470112,0.002054417,0.001169684,0.0008037661,0.00385209,0.00192512,0.003806671,0.02009576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004904203,"about_ca_system_score_gemma":0.001455092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006733882,"about_ca_topic_score_gemma":0.0009763025,"domain_scores_codex":[0.9975017,0.0004319004,0.0002829913,0.0007565392,0.000739309,0.0002876298],"domain_scores_gemma":[0.9958659,0.001452285,0.0004248553,0.00120795,0.0006958227,0.000353141],"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":[0.0008892874,0.0002818927,0.0006451144,0.0004494121,0.0001138726,0.0001592588,0.00004328114,0.0001987889,0.975632,0.001270848,0.002252563,0.01806365],"study_design_scores_gemma":[0.0001117316,0.0005211236,0.001922709,0.00006671063,0.0001542822,0.0009713558,0.00002853718,0.004092838,0.955625,0.000628948,0.03577004,0.0001067086],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09652989,0.002395267,0.8733587,0.001290102,0.002572272,0.0005671518,0.001360073,0.0178097,0.004116827],"genre_scores_gemma":[0.1222969,0.001865674,0.8333405,0.00330653,0.0005569485,0.00108775,0.003641678,0.003422087,0.03048194],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01837825,"threshold_uncertainty_score":0.06148142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02237478820971764,"score_gpt":0.3026890200037585,"score_spread":0.2803142317940409,"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."}}