{"id":"W2478691576","doi":"10.1016/j.carbpol.2016.08.012","title":"In-situ polymerized cellulose nanocrystals (CNC)—poly( l -lactide) (PLLA) nanomaterials and applications in nanocomposite processing","year":2016,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"biodegradable polymer synthesis and properties","field":"Materials Science","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"FPInnovations","funders":"","keywords":"Materials science; Nanomaterials; Nanocomposite; In situ polymerization; Extrusion; Polymer; Casting; Nanoparticle; Polymerization; Composite material; Nanotechnology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002864627,0.0002380439,0.0001684557,0.0001729738,0.0001808835,0.0003648447,0.0002078437,0.0002812835,0.0008501857],"category_scores_gemma":[0.0001975151,0.0001520306,0.0001630046,0.0001227031,0.0002275971,0.0003445867,0.00013626,0.0003378105,0.0002167893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006292318,"about_ca_system_score_gemma":0.0002859116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001341764,"about_ca_topic_score_gemma":0.002932741,"domain_scores_codex":[0.9998739,0.00001604971,0.000007908004,0.00002986636,0.00004443154,0.00002785009],"domain_scores_gemma":[0.9998895,0.0000432375,0.00002058604,0.000008019084,0.00002138171,0.00001732616],"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":[0.00002348014,0.00001560152,0.00003640645,0.00002154969,0.000001331935,0.00002021911,0.000006615756,0.0001012525,0.9982882,0.0001430894,0.00002162211,0.001320736],"study_design_scores_gemma":[0.000002628195,0.00002098776,0.0001602226,9.678348e-7,0.000001727975,0.00002166531,0.000004238511,0.0005870212,0.9986613,0.00001842889,0.0005187521,0.000001953498],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9631723,0.004250535,0.02305698,0.0002684144,0.00009474033,0.00005883756,0.0001321691,0.0001601333,0.008805958],"genre_scores_gemma":[0.9847789,0.001179519,0.01070405,0.00006499313,0.00002031746,0.00002756705,0.00007335401,0.0000316677,0.003119543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001341764,"threshold_uncertainty_score":0.004565418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01403666551479826,"score_gpt":0.2284784176173838,"score_spread":0.2144417521025855,"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."}}