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Record W2945538560 · doi:10.1139/er-2018-0109

Review of cytostatic wastewater degradation by ozone and advanced oxidation processes: results from Cuban studies

2019· article· en· W2945538560 on OpenAlexvenueno aff
P. García-Lario, O. Ledea Lozano, Eliet Véliz Lorenzo, Mayra Bataller Venta, Yalexmi Ramos Rodríguez, Carlos Castro, C. Gutiérrez Trujillo, Irán Fernández Torres

Bibliographic record

VenueEnvironmental Reviews · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsDispose patternAquatic environmentEnvironmental scienceEnvironmental chemistryBiochemical engineeringHuman healthWastewaterWaste managementEnvironmental engineeringChemistryBiologyEnvironmental healthEngineeringEcologyMedicine

Abstract

fetched live from OpenAlex

Among pharmaceuticals, cytostatics are a category of emerging contaminants that are of particular environmental concern, because of their mutagenic and carcinogenic characteristics. Concern about the presence of these drugs in the environment has increased in the last decades because of their potential harm to aquatic organisms and human health and their long-term cumulative impact on the environment, even at low concentrations in the order of ppb to ppt (μg/L to ng/L). In this paper we provide of an overview of the use of ozone and (or) advanced oxidation processes to eliminate cytostatics from the pharmaceutical wastewaters focusing on studies undertaken in Cuba. The review revealed that these treatments are suitable to degrade several antineoplastic drugs of different chemical structures and to safety dispose of wastewaters to the environment. In addition, we describe the analytical methods used for the determination of the fundamental by-products of applied treatments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.534
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.301
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2019
Admission routes1
Has abstractyes

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