{"id":"W1974226525","doi":"10.1002/ceat.201000237","title":"A Sequential Iterative Scheme for Design of Experiments in Complex Polymerizations","year":2010,"lang":"en","type":"article","venue":"Chemical Engineering & Technology","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Bayesian probability; Set (abstract data type); Design of experiments; Iterative and incremental development; Process (computing); Sequential analysis; Bayesian optimization; Optimal design; Scheme (mathematics); Experimental data; Mathematical optimization; Algorithm; Mathematics; Artificial intelligence; Machine learning","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":[0.0717209,0.002244539,0.002661948,0.001741158,0.001028176,0.001559476,0.002802019,0.001741044,0.005767384],"category_scores_gemma":[0.06277637,0.001714034,0.001814766,0.001362776,0.00269321,0.001625692,0.002807321,0.002591529,0.0009007604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002385016,"about_ca_system_score_gemma":0.004777845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001106799,"about_ca_topic_score_gemma":0.001801853,"domain_scores_codex":[0.9389857,0.04795607,0.002300392,0.00346087,0.006491265,0.0008056866],"domain_scores_gemma":[0.9426005,0.0451035,0.004079835,0.003107324,0.004339532,0.0007694329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00252563,0.0006417275,0.0009633656,0.001254906,0.0005193105,0.0001438362,0.0008900088,0.5859542,0.01753593,0.1635893,0.000835259,0.2251463],"study_design_scores_gemma":[0.0009683595,0.002367542,0.0003849268,0.0001132632,0.0001473956,0.00005947283,0.00003223294,0.8815565,0.007947123,0.1004009,0.005919335,0.0001031342],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001236387,0.00003620986,0.997749,0.00002210559,0.00001344965,0.0006044105,0.00001215221,0.00008007158,0.0002461984],"genre_scores_gemma":[0.03374812,0.00005524709,0.9625493,0.00003851806,0.00001233229,0.00323399,0.00002631563,0.00001878114,0.0003173416],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0717209,"threshold_uncertainty_score":0.3793009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01928877125667907,"score_gpt":0.2615384479296198,"score_spread":0.2422496766729408,"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."}}