{"id":"W4396889561","doi":"10.1021/acssusresmgt.4c00019","title":"Green Alginate Extraction from <i>Macrocystis pyrifera</i> for Bioplastic Applications: Physicochemical, Environmental Impact, and Chemical Hazard Analyses","year":2024,"lang":"en","type":"article","venue":"ACS Sustainable Resource Management","topic":"biodegradable polymer synthesis and properties","field":"Materials Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation; British Columbia Knowledge Development Fund; University of Victoria","keywords":"Bioplastic; Macrocystis pyrifera; Extraction (chemistry); Environmental hazard; Chemistry; Environmental science; Environmental chemistry; Pulp and paper industry; Waste management; Biology; Engineering; Botany; Kelp; Chromatography; Ecology","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":[0.0001918201,0.0002730189,0.0002556582,0.0001186865,0.0002730322,0.0004650613,0.0002415136,0.00008310626,0.0001336352],"category_scores_gemma":[0.000008822191,0.0002196669,0.0001086527,0.0001690796,0.0001665431,0.0002644587,0.0002630773,0.00009708956,0.0000573717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002145523,"about_ca_system_score_gemma":0.00001832841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003560032,"about_ca_topic_score_gemma":8.492199e-7,"domain_scores_codex":[0.9982894,0.00003797089,0.0002710224,0.0006485677,0.0002481093,0.0005049094],"domain_scores_gemma":[0.9992723,0.0001913972,0.0000698678,0.0003343746,0.00001743685,0.0001145545],"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":[0.0001653029,0.0001173147,0.00003184344,0.0008219128,0.0002118101,0.00003281072,0.0002357168,0.00002836315,0.9104338,0.0006741995,0.00330312,0.08394377],"study_design_scores_gemma":[0.0002696179,0.00005405517,0.00005446366,0.00007131297,0.0003331304,0.000008222853,0.001989679,0.00154648,0.8114066,0.00182682,0.1821108,0.0003288937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8932481,0.07612354,0.02568321,0.001228541,0.00007880443,0.001663694,0.0003576315,0.0003947455,0.001221759],"genre_scores_gemma":[0.9941096,0.0002701005,0.001184922,0.00009539608,0.0001866887,0.0007495581,0.0001126214,0.00004456122,0.003246549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1788077,"threshold_uncertainty_score":0.8957755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434634908477469,"score_gpt":0.271881606931853,"score_spread":0.2575352578470783,"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."}}