{"id":"W3016715848","doi":"10.1007/s40725-020-00117-4","title":"Advanced Applications for Lignin Micro- and Nano-based Materials","year":2020,"lang":"en","type":"article","venue":"Current Forestry Reports","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Lignin; Raw material; Nanofiber; Nanotechnology; Materials science; Renewable energy; Renewable resource; Polymer; Chemistry; Organic chemistry; Composite material; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003551535,0.0001276809,0.0001465279,0.00001157704,0.00004026593,0.00003005165,0.00005177098,0.00005531078,0.000006764457],"category_scores_gemma":[0.00001462531,0.0001310565,0.00003752032,0.00005473574,0.00002296609,0.00004108979,0.00001743556,0.0000533526,0.000003378734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001252998,"about_ca_system_score_gemma":0.00002332041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.873965e-7,"about_ca_topic_score_gemma":6.953384e-8,"domain_scores_codex":[0.9993002,0.000002223011,0.0002619781,0.0002145888,0.00006230475,0.0001586863],"domain_scores_gemma":[0.9996043,0.00001685698,0.00006054253,0.00016993,0.00002433915,0.0001239926],"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":[0.000003865608,0.00001805199,0.001044373,0.001040997,0.00001363726,0.00000670779,0.0000303322,0.0002336209,0.9787494,0.00002414715,0.01678744,0.002047447],"study_design_scores_gemma":[0.0001916475,0.00001106622,0.00003652052,0.00003742547,0.00001661994,0.00001494487,0.000008163148,0.0001653889,0.9304192,0.0001756522,0.06877635,0.0001470008],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880131,0.002974331,0.005258097,0.000215186,0.0008123218,0.001163139,0.0001639151,0.0006713536,0.0007284883],"genre_scores_gemma":[0.9976287,0.0000330505,0.001450417,0.00003191619,0.0002454584,0.0003733111,0.0001920415,0.00002826222,0.00001678584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05198891,"threshold_uncertainty_score":0.5344328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01379183613444769,"score_gpt":0.2393419529895416,"score_spread":0.2255501168550939,"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."}}