{"id":"W4392853787","doi":"10.1016/j.indcrop.2024.118370","title":"Red mud supported Ni-Cu bimetallic material for hydrothermal production of hydrogen from biomass","year":2024,"lang":"en","type":"article","venue":"Industrial Crops and Products","topic":"Bauxite Residue and Utilization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan; Lakehead University; Dalhousie University","funders":"National Natural Science Foundation of China","keywords":"Hydrothermal circulation; Biomass (ecology); Bimetallic strip; Hydrogen production; Production (economics); Hydrothermal synthesis; Chemistry; Red mud; Chemical engineering; Pulp and paper industry; Hydrogen; Nuclear chemistry; Materials science; Metallurgy; Biology; Agronomy; Catalysis; Biochemistry; Engineering; Organic chemistry; Economics","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":[0.00006893036,0.0002003267,0.0001671931,0.0002922634,0.0001874976,0.0002300094,0.0003570668,0.0002651683,0.000913622],"category_scores_gemma":[0.00009019305,0.0001494554,0.0001184472,0.00022456,0.0001015437,0.0002001768,0.0002921272,0.0002386848,0.0002724576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001705183,"about_ca_system_score_gemma":0.000133476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000325246,"about_ca_topic_score_gemma":0.000954884,"domain_scores_codex":[0.9999545,0.000005188592,0.0000039406,0.000008931171,0.00001590784,0.00001162359],"domain_scores_gemma":[0.9999759,0.000002735545,0.000004728317,0.000003023867,0.00000441609,0.000009162681],"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":[0.0001532524,0.00004452828,0.0002435554,0.0001544815,0.00001323649,0.0001696376,0.00002986316,0.000341157,0.9916044,0.0003892765,0.0002613182,0.00659538],"study_design_scores_gemma":[0.00001172457,0.0001630872,0.0009467867,0.00000631366,0.00001878562,0.0001163047,0.00003936236,0.002135413,0.9941754,0.00005892349,0.002320777,0.000007076995],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933108,0.0005891317,0.002496243,0.00007819168,0.00004500429,0.00001051923,0.0001129537,0.0001310971,0.003226013],"genre_scores_gemma":[0.9970583,0.000164938,0.00119248,0.00001056118,0.000005095153,0.000005460242,0.00007268508,0.000006932958,0.001483625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000913622,"threshold_uncertainty_score":0.003056347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03280467907357715,"score_gpt":0.2335166826474919,"score_spread":0.2007120035739147,"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."}}