{"id":"W3182809237","doi":"10.1073/pnas.2026452118","title":"Enzymatic depolymerization of highly crystalline polyethylene terephthalate enabled in moist-solid reaction mixtures","year":2021,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":152,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Depolymerization; Crystallinity; Polyethylene terephthalate; Terephthalic acid; Enzymatic hydrolysis; Materials science; Cutinase; Polyethylene; Hydrolysis; Chemical engineering; Amorphous solid; Organic chemistry; Cellulose; Yield (engineering); Chemistry; Polymer; Polyester; Composite material","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":[0.0004457034,0.00007803059,0.000142431,0.00009261708,0.0000755728,0.0000107243,0.0002668694,0.0000703827,0.00006480496],"category_scores_gemma":[0.0005438018,0.00005789379,0.00004179575,0.0008443233,0.0003792098,0.0002827038,0.0001124328,0.00009484428,0.000001183215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003305536,"about_ca_system_score_gemma":0.00002402154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005859083,"about_ca_topic_score_gemma":9.790019e-7,"domain_scores_codex":[0.9985311,0.0000113962,0.0004067133,0.0001950341,0.0007303539,0.0001253955],"domain_scores_gemma":[0.9993612,0.0001036998,0.0004662496,0.000009593853,0.0000340188,0.0000252274],"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":[0.000011053,0.0000569412,0.006389057,0.00003716092,0.000004433893,1.915574e-8,0.00011419,0.001506967,0.9897389,0.001938433,0.00001978761,0.0001830057],"study_design_scores_gemma":[0.0001267792,0.0000220223,0.1194832,0.00008183853,0.000008070247,0.000009990356,0.00004321895,0.003842559,0.8704406,0.00587448,0.00001526697,0.00005198611],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945651,0.0000674938,0.00003233115,0.0005265,0.00002085983,0.00008403514,0.00001560365,0.000003217749,0.004684908],"genre_scores_gemma":[0.9985537,0.00004237465,0.001253615,0.00004936192,0.00002019633,0.00000289298,6.309188e-7,0.000002927286,0.00007430735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1192983,"threshold_uncertainty_score":0.236084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01611543508473133,"score_gpt":0.2538341028122706,"score_spread":0.2377186677275392,"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."}}