{"id":"W2779107003","doi":"10.1016/j.polymertesting.2017.12.018","title":"Statistical design of sustainable thermoplastic blends of poly(glycerol succinate-co-maleate) (PGSMA), poly(lactic acid) (PLA) and poly(butylene succinate) (PBS)","year":2017,"lang":"en","type":"article","venue":"Polymer Testing","topic":"biodegradable polymer synthesis and properties","field":"Materials Science","cited_by":47,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Comisión Nacional de Investigación Científica y Tecnológica; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Ontario Ministry of Agriculture, Food and Rural Affairs; Ontario Research Foundation; University of Guelph","keywords":"Materials science; Ultimate tensile strength; Polybutylene succinate; Polypropylene; Izod impact strength test; Lactic acid; Glycerol; Composite material; Response surface methodology; Organic chemistry; Chromatography; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001298338,0.000592556,0.001010588,0.0002677701,0.001136885,0.0003427503,0.0009300431,0.0002398608,0.0006398833],"category_scores_gemma":[0.001991445,0.0004892617,0.00009639726,0.0002021512,0.0009643725,0.0007508943,0.0004178191,0.0002953768,0.00003720857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006566494,"about_ca_system_score_gemma":0.0003769319,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009966436,"about_ca_topic_score_gemma":0.00002954032,"domain_scores_codex":[0.9958975,0.0004035725,0.0009862374,0.0008030159,0.0006339794,0.001275705],"domain_scores_gemma":[0.995695,0.001609524,0.001022727,0.001084721,0.000266899,0.0003211372],"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":[0.0009776587,0.0002712423,0.04650434,0.0009903327,0.0001221056,0.0001325723,0.001133796,0.000001401077,0.8071869,0.004540881,0.00008518956,0.1380536],"study_design_scores_gemma":[0.0008682074,0.0005596054,0.01741275,0.0002669572,0.0002082709,0.0000943054,0.0006635207,0.001171314,0.9777573,0.0004156253,0.00002925504,0.0005529385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7668205,0.2128926,0.01175403,0.0007252902,0.0007121261,0.0006930685,0.0003507817,0.0002826826,0.005768933],"genre_scores_gemma":[0.9934888,0.00007496332,0.00504622,0.00004375429,0.0001417635,0.00004491904,0.000004619878,0.0000950466,0.001059923],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2266683,"threshold_uncertainty_score":0.9997559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.040279128013022,"score_gpt":0.2631930074654938,"score_spread":0.2229138794524718,"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."}}