{"id":"W4406230791","doi":"10.1016/j.jwpe.2024.106904","title":"Single nickel atoms doped into TiO2 decorating carbon quantum dots for boosting photodegradation of ciprofloxacin","year":2025,"lang":"en","type":"article","venue":"Journal of Water Process Engineering","topic":"Carbon and Quantum Dots Applications","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Photodegradation; Carbon quantum dots; Quantum dot; Nickel; Doping; Boosting (machine learning); Photochemistry; Materials science; Photocatalysis; Chemistry; Nanotechnology; Optoelectronics; Computer science; Metallurgy; Catalysis; Artificial intelligence; 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":[0.00007672652,0.0003257096,0.0001972837,0.000138331,0.0001211471,0.0002716372,0.0002829217,0.0004290659,0.0005636963],"category_scores_gemma":[0.0001129901,0.0001510526,0.0001976748,0.0001044001,0.0001776236,0.0002668498,0.0001693171,0.0002323239,0.000194729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000337881,"about_ca_system_score_gemma":0.0001414881,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008718378,"about_ca_topic_score_gemma":0.002172804,"domain_scores_codex":[0.9998935,0.000009871114,0.000009963424,0.00003218435,0.0000336658,0.00002075601],"domain_scores_gemma":[0.9999437,0.000006785713,0.00001562831,0.000008773011,0.00001589539,0.000009220186],"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":[0.00002317133,0.00001100462,0.0000413917,0.00002658641,0.00000263156,0.00001518108,0.000005060159,0.00006562276,0.9990832,0.00003034654,0.00001470371,0.0006811955],"study_design_scores_gemma":[0.000003741886,0.00007054242,0.0002639189,0.000001174534,0.000006873789,0.00001977612,0.000004734344,0.0008278241,0.9982748,0.000006013795,0.0005178724,0.000002815708],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909422,0.001053932,0.006182916,0.00006978048,0.0000473863,0.00004799565,0.00008682292,0.00009569449,0.001473353],"genre_scores_gemma":[0.9927227,0.0003923643,0.00504399,0.00002913123,0.000007576831,0.00002067291,0.00007079312,0.00001420232,0.001698737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008718378,"threshold_uncertainty_score":0.002451539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269153599018398,"score_gpt":0.2650367744242983,"score_spread":0.2523452384341144,"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."}}