{"id":"W4417210918","doi":"10.1016/j.progpolymsci.2025.102064","title":"Progress in bioplastics blends, compatibilization, modifications, and AI-driven innovations for material applications","year":2025,"lang":"en","type":"article","venue":"Progress in Polymer Science","topic":"biodegradable polymer synthesis and properties","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Bioplastic; Process (computing); Compatibilization; Work (physics); Key (lock); Biomimetics","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":[0.001066551,0.0007609701,0.0006583595,0.001007036,0.0002679022,0.001271948,0.0004739641,0.0007450485,0.001826553],"category_scores_gemma":[0.0007598393,0.0004435505,0.0006117608,0.001015396,0.0005395022,0.001948511,0.0007700234,0.001468422,0.0009560716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006142675,"about_ca_system_score_gemma":0.000733148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003125801,"about_ca_topic_score_gemma":0.0005299895,"domain_scores_codex":[0.9995431,0.000070659,0.00005449575,0.0001056687,0.0001921414,0.00003392895],"domain_scores_gemma":[0.9997386,0.0001196108,0.00006399155,0.00002110246,0.00004070585,0.00001585707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001334913,0.0002263004,0.0006711186,0.02248919,0.0001544371,0.0003833154,0.0002832781,0.009394027,0.3868771,0.07459406,0.003338967,0.5014547],"study_design_scores_gemma":[0.00003257388,0.000737112,0.001343985,0.002233927,0.0002480038,0.001101419,0.0001278355,0.01036851,0.2839112,0.02096636,0.6788294,0.00009974577],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03742636,0.8751207,0.06308167,0.001619564,0.0005207815,0.000114541,0.000201935,0.0003623194,0.02155203],"genre_scores_gemma":[0.1401706,0.8085673,0.04531068,0.000670375,0.0003608314,0.0001589179,0.0002297233,0.0001130748,0.004418424],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.001826553,"threshold_uncertainty_score":0.00611043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209078349685629,"score_gpt":0.2980451852542434,"score_spread":0.2759544017573871,"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."}}