{"id":"W3006494453","doi":"10.1016/j.carbpol.2020.115998","title":"Photopolymerized Starchstarch Nanoparticle (SNP) network hydrogels","year":2020,"lang":"en","type":"article","venue":"Carbohydrate Polymers","topic":"Hydrogels: synthesis, properties, applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"EcoSynthetix (Canada); McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Standards and Technology; U.S. Department of Commerce; National Science Foundation","keywords":"Self-healing hydrogels; Starch; Crystallinity; Chemical engineering; Materials science; Polymerization; Nanoparticle; Polymer; Chemistry; Nanotechnology; Polymer chemistry; Composite material; Biochemistry","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":[0.000081224,0.0001510016,0.00007570229,0.00009200574,0.00005926006,0.0001245893,0.00008984393,0.0001421468,0.00116849],"category_scores_gemma":[0.00008842164,0.00007642282,0.00007941882,0.00007958281,0.00008740742,0.0002088705,0.0001011651,0.0002361498,0.0001745442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136838,"about_ca_system_score_gemma":0.00007100701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002004016,"about_ca_topic_score_gemma":0.0005664436,"domain_scores_codex":[0.9999557,0.000004385703,0.000002812686,0.0000136825,0.00001265506,0.00001072124],"domain_scores_gemma":[0.9999385,0.00001647145,0.00001903606,0.000004286945,0.000008446008,0.00001320885],"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":[0.0000231023,0.000007583991,0.00003632488,0.00001798614,0.00000137557,0.00002136234,0.000009518836,0.000146419,0.9984303,0.00008803672,0.00003204862,0.001185927],"study_design_scores_gemma":[0.000003155823,0.00007492151,0.0004146535,0.000002227122,0.000003255907,0.00002833656,0.000005999631,0.0008199737,0.9979657,0.0000193264,0.0006600583,0.000002410156],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930547,0.0003632456,0.003571207,0.00005460479,0.00002319633,0.00001260706,0.00009284745,0.00005730168,0.002770384],"genre_scores_gemma":[0.9942075,0.0002418419,0.002692201,0.00003639527,0.000006902291,0.00001374402,0.00005875677,0.00001493971,0.002727677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00116849,"threshold_uncertainty_score":0.003908992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02317830332614885,"score_gpt":0.2461904828007565,"score_spread":0.2230121794746077,"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."}}