{"id":"W2889512441","doi":"10.1155/2018/8742094","title":"Chemicals, Materials, and Catalysts from Natural Renewable Lignocelluloses","year":2018,"lang":"en","type":"article","venue":"International Journal of Polymer Science","topic":"Catalysis for Biomass Conversion","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; University of New Brunswick","funders":"","keywords":"Renewable energy; Materials science; Catalysis; Natural (archaeology); Composite material; Business; Polymer science; Engineering; Chemistry; Organic chemistry; Geology","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":[0.0001674526,0.0002723493,0.0001420846,0.0005973544,0.0002529371,0.0004865646,0.0002678432,0.0002821145,0.002151726],"category_scores_gemma":[0.0002114599,0.0001740473,0.000157312,0.0002807688,0.0002765914,0.0005381457,0.0002876146,0.0004312375,0.0007258405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000399118,"about_ca_system_score_gemma":0.0002833158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008738222,"about_ca_topic_score_gemma":0.002792898,"domain_scores_codex":[0.9998888,0.000009152286,0.000007796812,0.00001118799,0.000058625,0.00002443749],"domain_scores_gemma":[0.9999634,0.00001043574,0.000005120942,0.000008072238,0.000007651202,0.000005316123],"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":[0.0001959059,0.0001639308,0.001568746,0.001214844,0.000039491,0.0004956024,0.00008084294,0.00346065,0.8959994,0.02949055,0.00162185,0.06566818],"study_design_scores_gemma":[0.00001002516,0.00007406028,0.00167409,0.00004134998,0.00001340814,0.0002199909,0.00005997327,0.001158389,0.9680577,0.003889679,0.02479305,0.000008273252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8669142,0.06283258,0.01212109,0.001226692,0.0003234956,0.00005798545,0.0009491474,0.0002193568,0.05535543],"genre_scores_gemma":[0.9672073,0.01466331,0.003291665,0.000109866,0.00006773284,0.00002540068,0.0006395589,0.00002378163,0.01397143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002151726,"threshold_uncertainty_score":0.007198274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004037621192248804,"score_gpt":0.2142248649192487,"score_spread":0.2101872437269999,"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."}}