{"id":"W4409619355","doi":"10.1007/s11270-025-07967-3","title":"Development of Agro-Based Engineered Biochars for Low Concentration Nitrate Adsorption: Modification Selection, Performance, Factors, Mechanism, and Reliability","year":2025,"lang":"en","type":"article","venue":"Water Air & Soil Pollution","topic":"Phosphorus and nutrient management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Selection (genetic algorithm); Adsorption; Biochar; Mechanism (biology); Reliability (semiconductor); Nitrate; Reliability engineering; Chemical engineering; Chemistry; Environmental science; Computer science; Materials science; Engineering; Machine learning; Organic chemistry; Pyrolysis; Thermodynamics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002844941,0.0001230661,0.0001095448,0.00004587094,0.0001733081,0.00001435198,0.00006655061,0.0000618821,0.00003178142],"category_scores_gemma":[0.000006404619,0.00009961042,0.00003276683,0.0001651601,0.00005209797,0.0001865838,0.00003154244,0.00004024069,0.000008835151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002696319,"about_ca_system_score_gemma":0.00002298597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004319896,"about_ca_topic_score_gemma":0.00001567141,"domain_scores_codex":[0.9990842,0.00002070834,0.0002865633,0.0002637365,0.000152044,0.0001927977],"domain_scores_gemma":[0.999743,0.000006846006,0.0000666078,0.0001166413,0.00002971541,0.00003715738],"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":[0.0003442533,0.0003845404,0.01364527,0.0003382005,0.00003916925,5.315344e-8,0.001567994,0.04998134,0.9244326,0.001489936,0.0005844485,0.007192189],"study_design_scores_gemma":[0.0005234732,0.00005391658,0.05950569,0.00002659221,0.00001923331,6.52101e-8,0.00003130153,0.06868005,0.8693584,0.0004954594,0.001194342,0.0001115187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9197723,0.000008473692,0.07926696,0.0002046737,0.000119259,0.0004997916,0.000009729478,0.00003826976,0.00008057912],"genre_scores_gemma":[0.9976427,0.00001404888,0.001888996,0.00006488991,0.000008418582,0.0000892274,0.0001251983,0.000005974886,0.0001605599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07787042,"threshold_uncertainty_score":0.4061995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007075500088191231,"score_gpt":0.1984636452888717,"score_spread":0.1913881452006805,"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."}}