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Record W7005484695

Removal of pharmaceutically active compounds from water systems using freeze concentration / by Yuanyuan Shao.

2007· dissertation· en· W7005484695 on OpenAlexfundno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2007
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
FundersLakehead University
KeywordsWastewaterEffluentDrugHuman healthSewage treatmentSurface water
DOInot available

Abstract

fetched live from OpenAlex

"In the last few years, there has been a growing concern in the occurrence of pharmaceutically active compounds in the aquatic environment. Just in Europe, more than 3000 prescription and non-prescription drugs are used by human and animals and more than 80 drugs have been detected in municipal wastewater treatment plant effluent, surface water, groundwater, and in a few isolated cases, in drinking water, some at alarmingly high concentrations. Although no known human health effects have been associated with exposure to drinking water containing trace concentrations of drug residues, there is concrete evidence that these drug residues could cause numerous adverse health effects on aquatic life, even at very low concentrations. Municipal wastewater treatment plant effluents have been identified as the major source of drug residues in surface waters. Conventional wastewater treatment systems cannot effectively remove pharmaceutically active compounds. The suitability of distinct wastewater treatment processes for the elimination of drug residues has not been studied. Freezing has been used successfully to treat various wastewaters.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.057
GPT teacher head0.273
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2007
Admission routes1
Has abstractyes

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