{"id":"W3124993896","doi":"10.1007/s12649-020-01335-4","title":"Coagulation Efficiency of Biomass Fly Ash Leachate in Thermomechanical Pulping (TMP) Pressate","year":2021,"lang":"en","type":"article","venue":"Waste and Biomass Valorization","topic":"Lignin and Wood Chemistry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Alum; Fly ash; Pulp and paper industry; Chemistry; Coagulation; Leachate; Chemical oxygen demand; Chemical engineering; Nuclear chemistry; Materials science; Waste management; Wastewater; Environmental chemistry; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001791736,0.000182149,0.0001827588,0.0002084217,0.000207405,0.0002881599,0.0001174148,0.0002401547,0.001809565],"category_scores_gemma":[0.0002304342,0.00008869915,0.0002558771,0.0001372325,0.0001157817,0.0002173806,0.0001379248,0.0002214933,0.00037993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003000437,"about_ca_system_score_gemma":0.0002570626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002377029,"about_ca_topic_score_gemma":0.003579748,"domain_scores_codex":[0.999853,0.00002147864,0.00001219376,0.00002707282,0.00004684598,0.00003946611],"domain_scores_gemma":[0.9999108,0.00002446142,0.00001175742,0.000005311972,0.00003476108,0.000012752],"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":[0.000541943,0.00003326498,0.001071081,0.00004487161,0.00001237268,0.00002767953,0.00003877183,0.0004299522,0.9947479,0.00006128124,0.00005160359,0.00293935],"study_design_scores_gemma":[0.000003863727,0.0001269799,0.00266968,0.000001839497,0.000006443602,0.00001310123,0.00002543085,0.001009534,0.9959232,0.00001016779,0.0002072422,0.000002555909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985805,0.0001745644,0.0004275023,0.00001155758,0.00000570877,0.00000498946,0.00008840006,0.00001130355,0.0006955969],"genre_scores_gemma":[0.9970813,0.0001198872,0.0002284798,0.000009785938,0.000002195308,0.000004263239,0.0001060879,0.000006043299,0.002441834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002377029,"threshold_uncertainty_score":0.006053627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01017060385324599,"score_gpt":0.2028148665688859,"score_spread":0.1926442627156399,"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."}}