{"id":"W2900031081","doi":"10.1021/acsomega.8b01675","title":"Bio-poly(butylene succinate) and Its Composites with Grape Pomace: Mechanical Performance and Thermal Properties","year":2018,"lang":"en","type":"article","venue":"ACS Omega","topic":"Natural Fiber Reinforced Composites","field":"Materials Science","cited_by":134,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph","keywords":"Pomace; Materials science; Thermogravimetric analysis; Flexural strength; Composite material; Molding (decorative); Compression molding; Maleic anhydride; Extrusion; Composite number; Polybutylene succinate; Izod impact strength test; Mold; Polymer; Chemistry; Food science; Ultimate tensile strength","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":[],"consensus_categories":[],"category_scores_codex":[0.0001551275,0.0002224535,0.0002269709,0.00007448476,0.000309987,0.0001757205,0.0002443127,0.00008382865,0.00001915697],"category_scores_gemma":[0.00001494068,0.0001421499,0.00001496823,0.0001665582,0.0002444697,0.0005778777,0.0002356553,0.0001272457,0.00007435849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001709833,"about_ca_system_score_gemma":0.00002210906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002589061,"about_ca_topic_score_gemma":0.000005815968,"domain_scores_codex":[0.998815,0.00003997246,0.0001837248,0.0003490423,0.0002434676,0.0003688066],"domain_scores_gemma":[0.9994211,0.00003943424,0.00007444852,0.000213206,0.0001326226,0.000119165],"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":[0.0002464086,0.00001157092,0.001537176,0.0000530095,0.00001294784,0.000004307265,0.0002656765,0.000001937125,0.9961711,0.0007776984,0.00002029509,0.0008978534],"study_design_scores_gemma":[0.0005160265,0.0007765435,0.004977918,0.00008909415,0.00002376667,0.0001232495,0.00002025984,0.001173549,0.9917654,0.00004444037,0.0002303456,0.0002594318],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968323,0.002012605,0.00000963013,0.0003757733,0.00009840968,0.0002412746,0.000005334958,0.0001243682,0.000300308],"genre_scores_gemma":[0.9983585,0.00006627398,0.0009207143,0.0001963207,0.0001007599,0.00001346371,0.000002449124,0.0000223285,0.0003191638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004405744,"threshold_uncertainty_score":0.5796707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173154545612036,"score_gpt":0.2128492686408518,"score_spread":0.2011177231847314,"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."}}