{"id":"W2111591386","doi":"10.1002/mren.201400048","title":"Design of Optimal Experiments for Terpolymerization Reactivity Ratio Estimation","year":2015,"lang":"en","type":"article","venue":"Macromolecular Reaction Engineering","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reactivity (psychology); Heuristics; Chemistry; Mathematics; Optimal design; Composition (language); Thermodynamics; Statistics; Mathematical optimization; Physics","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":[0.005946608,0.00170146,0.002201884,0.0009805135,0.0004138983,0.00139278,0.001121939,0.001367065,0.002028181],"category_scores_gemma":[0.009893504,0.001016537,0.001128843,0.0004336606,0.0008780892,0.0007559752,0.0009831233,0.001782565,0.0002619115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001148015,"about_ca_system_score_gemma":0.002703055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007797547,"about_ca_topic_score_gemma":0.0007899691,"domain_scores_codex":[0.9968435,0.001813302,0.0001085712,0.0005534737,0.0003684919,0.000312633],"domain_scores_gemma":[0.9933099,0.004878087,0.0008600578,0.0002825523,0.0005016933,0.0001677657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001330642,0.0006507658,0.0007595072,0.0005296479,0.0001223399,0.00006718175,0.00006951499,0.9244941,0.0220906,0.0106835,0.0002870997,0.03891513],"study_design_scores_gemma":[0.0001879309,0.0009140426,0.0003379733,0.00002444916,0.00005695862,0.00001275149,0.00002204951,0.9760651,0.01688979,0.004721126,0.0007439286,0.00002394054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04474419,0.000250156,0.9526107,0.00009013442,0.00003690787,0.0006562652,0.00007520542,0.0003065481,0.001229957],"genre_scores_gemma":[0.5820654,0.0002218688,0.4142638,0.00009877799,0.00001795629,0.002590322,0.0001210505,0.00005116867,0.0005696251],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005946608,"threshold_uncertainty_score":0.03144902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1416078855675469,"score_gpt":0.4026099270860546,"score_spread":0.2610020415185078,"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."}}