{"id":"W2895065152","doi":"10.1016/j.jhazmat.2018.09.070","title":"Acid-treated clay catalysts for organic dye ozonation – Thorough mineralization through optimum catalyst basicity and hydrophilic character","year":2018,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; University of Queensland; Ministère du Développement Économique, de l’Innovation et de l’Exportation","keywords":"Catalysis; Chemistry; Adsorption; Methyl orange; Methylene blue; Montmorillonite; Mineralization (soil science); Desorption; Inorganic chemistry; Molecule; Ion exchange; Organic chemistry; Ion; Photocatalysis","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":[0.0001414038,0.0002920957,0.0001448769,0.0001861035,0.000133483,0.0002839954,0.0001984924,0.0003095117,0.0009532193],"category_scores_gemma":[0.0002564063,0.0001613846,0.000167841,0.0001329188,0.0001669424,0.0003256655,0.0002531568,0.0003682218,0.0002621906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002026304,"about_ca_system_score_gemma":0.0001938775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006937928,"about_ca_topic_score_gemma":0.00206429,"domain_scores_codex":[0.9999006,0.000008718629,0.00001127073,0.00001606376,0.00003357164,0.00002969771],"domain_scores_gemma":[0.9999264,0.00001294232,0.0000171939,0.000006819792,0.00002099576,0.00001568151],"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":[0.0001398214,0.00002000754,0.0001383396,0.00003846453,0.000005432659,0.00003205891,0.00002231532,0.000111209,0.9970399,0.00009213014,0.00004951281,0.00231082],"study_design_scores_gemma":[0.000005720373,0.00008936878,0.0005906319,0.000002629599,0.00001045518,0.00004040825,0.00001627266,0.0005649261,0.9979418,0.00001790913,0.0007162059,0.000003676206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959265,0.0005049148,0.001928326,0.00004502389,0.00002007835,0.00001401455,0.00007043752,0.00004306317,0.001447675],"genre_scores_gemma":[0.9985089,0.0001608303,0.0004920441,0.000007514254,0.000003056471,0.000003357526,0.00005822333,0.00000734897,0.0007586527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009532193,"threshold_uncertainty_score":0.003188848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01254272418989143,"score_gpt":0.255812030543944,"score_spread":0.2432693063540526,"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."}}