{"id":"W4408215542","doi":"10.70176/3007-973x.1023","title":"Thermal Carbonization of Biomass Wood Dust and Algae Wastes <i>via</i> Microwave-Assisted H<sub>3</sub>PO<sub>4</sub>: Desirability Function and Statistical Optimization for Methylene Blue Dye Removal","year":2025,"lang":"en","type":"article","venue":"AUIQ complementary biological system.","topic":"Thermochemical Biomass Conversion Processes","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Carbonization; Biomass (ecology); Algae; Microwave; Pulp and paper industry; Environmental science; Waste management; Chemistry; Materials science; Animal science; Botany; Biology; Agronomy; Engineering; Composite material; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001419861,0.001149351,0.001619389,0.0004426749,0.0005370077,0.0001780136,0.0006534006,0.0008408203,0.0001950395],"category_scores_gemma":[0.0004250532,0.001024573,0.0003005371,0.001175853,0.0006507696,0.0003799555,0.0005885927,0.0003421847,0.00001382929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007038304,"about_ca_system_score_gemma":0.0001226022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003617526,"about_ca_topic_score_gemma":0.0001410059,"domain_scores_codex":[0.9933234,0.0008159799,0.00223721,0.001717239,0.0006989854,0.001207222],"domain_scores_gemma":[0.9959705,0.001549117,0.0006240321,0.0007627672,0.0006335718,0.0004599459],"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":[0.0009186802,0.0003456693,0.001123052,0.002264254,0.0007352183,0.0000169855,0.0001057938,0.00062674,0.9817923,0.002431153,0.000843705,0.008796414],"study_design_scores_gemma":[0.006313435,0.001266428,0.0195795,0.0006679048,0.001125801,0.00007800654,0.000325548,0.05673197,0.908717,0.0007064848,0.002609794,0.001878155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8614525,0.003720175,0.1290868,0.0002260344,0.0008746914,0.002482652,0.001288514,0.0006518015,0.0002168791],"genre_scores_gemma":[0.9861449,0.0003410673,0.009873694,0.0001249517,0.0002631506,0.0002894366,0.002827718,0.0001164243,0.00001867137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1246925,"threshold_uncertainty_score":0.9992205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01741481285979016,"score_gpt":0.2204612263623219,"score_spread":0.2030464135025318,"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."}}