{"id":"W4411980506","doi":"10.1016/j.jwpe.2025.108164","title":"Structural and adsorptive comparison of activated hydrochar and biochar: Machine learning analysis and novel driven kinetic and thermodynamic insight","year":2025,"lang":"en","type":"article","venue":"Journal of Water Process Engineering","topic":"Adsorption and biosorption for pollutant removal","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Biochar; Adsorption; Chemistry; Kinetic energy; Activated carbon; Materials science; Physical chemistry; Organic chemistry; Physics","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":[0.0001564514,0.0001570521,0.0001362755,0.0003726462,0.0001508817,0.0002076818,0.0002895934,0.0002172486,0.001507669],"category_scores_gemma":[0.0002307334,0.0001132412,0.0002456532,0.0001950218,0.000239309,0.0002577109,0.0001049032,0.0003008231,0.0001569587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002604294,"about_ca_system_score_gemma":0.0002011487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054756,"about_ca_topic_score_gemma":0.001962814,"domain_scores_codex":[0.9999475,0.000005865862,0.00000279144,0.0000107844,0.00002328399,0.000009783839],"domain_scores_gemma":[0.9998924,0.00002980838,0.00001579002,0.00001071936,0.00004272212,0.000008705539],"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":[0.0004363514,0.0001915333,0.005348823,0.0001328097,0.00003830147,0.00008795919,0.00006952718,0.02450615,0.9451614,0.003350627,0.0002315556,0.02044488],"study_design_scores_gemma":[0.00001878306,0.0005000613,0.02648838,0.000007315228,0.00004121062,0.000126927,0.0001586002,0.2935883,0.6757405,0.001893769,0.001404235,0.0000319899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942471,0.0001402109,0.004325982,0.00004185626,0.00000594913,0.000008473105,0.0001829991,0.00004701939,0.001000423],"genre_scores_gemma":[0.9981786,0.00005008951,0.001055429,0.000009821067,0.000001980913,0.000003391708,0.0001986505,0.000005417629,0.0004965244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001507669,"threshold_uncertainty_score":0.005043685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005698452396626827,"score_gpt":0.2209900504156248,"score_spread":0.2152915980189979,"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."}}