{"id":"W4319058744","doi":"10.1002/adma.202209685","title":"Versatile Assembly of Metal–Phenolic Network Foams Enabled by Tannin–Cellulose Nanofibers","year":2023,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"European Research Council; European Commission; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Canada Excellence Research Chairs, Government of Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Canada Foundation for Innovation","keywords":"Materials science; Nanofiber; Cellulose; Tannin; Metal; Nanotechnology; Polymer science; Composite material; Chemical engineering; Metallurgy","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":[0.000121614,0.0002964225,0.0001375817,0.0002484278,0.0001372786,0.00016003,0.0001608929,0.0002495814,0.0006816806],"category_scores_gemma":[0.000149402,0.0001233075,0.0001758802,0.0001125112,0.0001322239,0.0002370119,0.0002106939,0.0001667183,0.0002064233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002085114,"about_ca_system_score_gemma":0.00007325281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003985761,"about_ca_topic_score_gemma":0.0009972693,"domain_scores_codex":[0.9999148,0.000008313519,0.000005687306,0.00002569379,0.00002019289,0.00002533613],"domain_scores_gemma":[0.9999194,0.00001562522,0.00002406824,0.000008790713,0.00001374093,0.00001837421],"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":[0.00002200918,0.000009543457,0.00005584327,0.0000313635,0.000004051987,0.00004181454,0.00002299145,0.0002061551,0.9975811,0.00009532265,0.00004251975,0.001887366],"study_design_scores_gemma":[0.000004364405,0.00005948116,0.0006366085,0.000004028823,0.000005280562,0.00003669204,0.000009320724,0.001526612,0.9961934,0.00002986685,0.001489541,0.000004806517],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870098,0.0006827097,0.00926693,0.00004560768,0.00003208742,0.00003334337,0.0001700806,0.0002702335,0.002489214],"genre_scores_gemma":[0.9921718,0.0002190108,0.006157183,0.00002016224,0.000009628327,0.00002613036,0.0001059096,0.00002365648,0.001266602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006816806,"threshold_uncertainty_score":0.002280414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006162186668761818,"score_gpt":0.2074910795587747,"score_spread":0.2013288928900129,"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."}}