{"id":"W4225927450","doi":"10.1039/d2gc00573e","title":"Upcycling agro-industrial blueberry waste into platform chemicals and structured materials for application in marine environments","year":2022,"lang":"en","type":"article","venue":"Green Chemistry","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Comisión Nacional de Investigación Científica y Tecnológica; European Research Council; Aalto-Yliopisto; Canada Foundation for Innovation; Academy of Finland; Canada Excellence Research Chairs, Government of Canada","keywords":"Waste management; Environmental science; Business; Process engineering; Nanotechnology; Materials science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001512544,0.0001913054,0.0002249882,0.000019014,0.00007571197,0.00002128625,0.0001909515,0.0001641138,0.0001143355],"category_scores_gemma":[0.00001263177,0.0002263675,0.00003486484,0.00007156369,0.00002870808,0.00005574429,0.0002168927,0.0002293216,0.00000124523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451508,"about_ca_system_score_gemma":0.00001337956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004134922,"about_ca_topic_score_gemma":0.000002501397,"domain_scores_codex":[0.9989534,0.000003747507,0.0003181888,0.0002834059,0.0001901975,0.0002510602],"domain_scores_gemma":[0.9995926,0.00003171977,0.00006355029,0.0002284235,0.000005110045,0.00007861421],"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":[0.00002666188,0.00001390424,0.0004942287,0.000217512,0.0000245214,0.000002004565,0.00009775494,0.0001900349,0.9963589,0.000001696678,0.0004314353,0.002141366],"study_design_scores_gemma":[0.001170381,0.000006143498,0.00002461018,0.00001105873,0.00001548348,0.0000121593,0.0001778791,0.0004838466,0.9951054,0.000519029,0.002239051,0.0002349592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987891,0.00004796431,0.00002452148,0.00003422504,0.00009168312,0.0002383145,0.00009880424,0.00006364772,0.0006117892],"genre_scores_gemma":[0.9982519,0.00001115561,0.000294938,0.00001856296,0.0003879635,0.0002976069,0.000419708,0.00004036078,0.0002777655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001906406,"threshold_uncertainty_score":0.9230997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008653120470412954,"score_gpt":0.1954006076696335,"score_spread":0.1867474871992205,"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."}}