{"id":"W2644617923","doi":"10.1021/acssuschemeng.7b00615","title":"Cost Reduction and Mechanical Enhancement of Biopolyesters Using an Agricultural Byproduct from Konjac Glucomannan Processing","year":2017,"lang":"en","type":"article","venue":"ACS Sustainable Chemistry & Engineering","topic":"biodegradable polymer synthesis and properties","field":"Materials Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Ministry of Education of the People's Republic of China; Office of Energy Research and Development; Chongqing Science and Technology Commission; National Natural Science Foundation of China","keywords":"Ultimate tensile strength; Materials science; Elongation; Composite material; Raw material; Compression molding; Degradation (telecommunications); Polybutylene succinate; Biodegradation; Compressive strength; Izod impact strength test; Chemical engineering; Chemistry; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001259628,0.0005228624,0.0001513008,0.0002621843,0.0001045959,0.0002250397,0.0001376424,0.0002490489,0.000328861],"category_scores_gemma":[0.000112607,0.0001212035,0.0002762353,0.0001959678,0.0001308575,0.0003074657,0.000185582,0.0003544487,0.0001321254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001520472,"about_ca_system_score_gemma":0.0001545074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003240569,"about_ca_topic_score_gemma":0.001003279,"domain_scores_codex":[0.9999118,0.000009338301,0.000008473648,0.00001629266,0.00003109521,0.00002298428],"domain_scores_gemma":[0.9999372,0.000009995199,0.00002431307,0.000005897459,0.00001216576,0.00001047009],"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":[0.0000110715,0.00001071347,0.00005512324,0.00002203037,0.000001433146,0.00002578973,0.000004622407,0.00006335456,0.9986511,0.0000324314,0.00000386944,0.001118494],"study_design_scores_gemma":[0.000001207577,0.00005993388,0.0005452959,0.000001869459,0.00000397208,0.00002678671,0.000005106482,0.0002845624,0.998833,0.000009527107,0.0002272133,0.00000161146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9937616,0.0008709956,0.004249365,0.00003428607,0.00001359824,0.0000224782,0.00004682455,0.00002662492,0.00097425],"genre_scores_gemma":[0.9918917,0.0007666926,0.006433842,0.00002345775,0.000006592087,0.00002061919,0.00007001754,0.00001205922,0.0007749755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005228624,"threshold_uncertainty_score":0.001103222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02522750089311122,"score_gpt":0.2396304137729868,"score_spread":0.2144029128798756,"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."}}