MétaCan
Menu
Back to cohort
Record W4224992885 · doi:10.3389/fmicb.2022.869332

Pharmaceutical Pollution in Aquatic Environments: A Concise Review of Environmental Impacts and Bioremediation Systems

2022· review· en· W4224992885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Microbiology · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsUniversity of Manitoba
FundersAgencia Estatal de InvestigaciónJunta de Castilla y LeónMinisterio de Economía y CompetitividadConsejo Nacional de Ciencia y TecnologíaHelsingin Yliopisto
KeywordsBioremediationEnvironmental remediationEnvironmental scienceEnvironmental planningHuman healthPollutionBiochemical engineeringSewage treatmentWastewaterContaminationEnvironmental protectionWaste managementEnvironmental engineeringBiologyEcologyEngineeringEnvironmental health

Abstract

fetched live from OpenAlex

The presence of emerging contaminants in the environment, such as pharmaceuticals, is a growing global concern. The excessive use of medication globally, together with the recalcitrance of pharmaceuticals in traditional wastewater treatment systems, has caused these compounds to present a severe environmental problem. In recent years, the increase in their availability, access and use of drugs has caused concentrations in water bodies to rise substantially. Considered as emerging contaminants, pharmaceuticals represent a challenge in the field of environmental remediation; therefore, alternative add-on systems for traditional wastewater treatment plants are continuously being developed to mitigate their impact and reduce their effects on the environment and human health. In this review, we describe the current status and impact of pharmaceutical compounds as emerging contaminants, focusing on their presence in water bodies, and analyzing the development of bioremediation systems, especially mycoremediation, for the removal of these pharmaceutical compounds with a special focus on fungal technologies.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.306
Teacher spread0.277 · 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