{"id":"W1975722170","doi":"10.1016/j.compchemeng.2004.06.017","title":"An enhanced pseudo-binary-mixture (PBM) algorithm for multistage separation processes","year":2004,"lang":"en","type":"article","venue":"Computers & Chemical Engineering","topic":"Field-Flow Fractionation Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ideal (ethics); Algorithm; Binary number; Convergence (economics); Scale (ratio); Computer science; Separation (statistics); Algebraic number; Mathematics; Mathematical optimization; Arithmetic","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004927954,0.0002288075,0.0001878129,0.00009848836,0.00003808415,0.00005938733,0.0002014693,0.0001852284,0.000006691288],"category_scores_gemma":[0.00003726245,0.0002696022,0.000057101,0.0002114344,0.00001297413,0.0003992455,0.00001882625,0.0002182514,0.000004790547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000191889,"about_ca_system_score_gemma":0.00002276708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002470958,"about_ca_topic_score_gemma":4.245308e-7,"domain_scores_codex":[0.9991017,0.000002575139,0.0002343663,0.0002595765,0.0001394215,0.0002623409],"domain_scores_gemma":[0.9994984,0.00007371813,0.00002856596,0.0001930565,0.0001021393,0.0001041778],"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":[0.000003129182,0.00003407319,3.463987e-7,0.0001947815,0.0000196305,0.000002315628,0.0001655925,0.3968451,0.5887068,0.0001348615,0.0003082089,0.01358517],"study_design_scores_gemma":[0.0002681377,0.00002806608,0.000004180805,0.00004674799,0.00000527981,0.000005035406,0.000003778481,0.4875326,0.5111425,0.00008061477,0.0006932346,0.0001898204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03949913,0.00008368678,0.9576757,0.00003951649,0.0003879897,0.000306925,0.00001507439,0.001952057,0.00003993804],"genre_scores_gemma":[0.5665424,0.00001192427,0.4328818,0.00003333208,0.0002511466,0.0001189143,0.000105011,0.00004911474,0.000006302598],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5270433,"threshold_uncertainty_score":0.9999756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005197917996568767,"score_gpt":0.2379511502016731,"score_spread":0.2327532322051044,"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."}}