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Record W4319864397 · doi:10.5267/j.ccl.2022.11.003

Performance of a variety of treatment processes to purify wastewater in the food industry

2023· article· en· W4319864397 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCurrent Chemistry Letters · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring Technologies
Canadian institutionsnot available
FundersStrong
KeywordsWastewaterEffluentChemical oxygen demandBiochemical oxygen demandChemistryFood industryTotal suspended solidsSewage treatmentPulp and paper industryWastewater quality indicatorsSuspended solidsWaste managementEnvironmental scienceEnvironmental engineeringFood science

Abstract

fetched live from OpenAlex

The food industry consumes large amounts of water although there is an increasing demand for water and a rapid decrease in the level of natural water resources. Wastewater resulting from food industries needs to be assessed for their compliance to standards. In this study, wastewater treatment steps from the food industry were investigated for accurate assessment of wastewater loading by analyzing parameters of the concentration of compounds present in the effluents. The results revealed that the parameters of treated wastewater were as follow, electrical conductivity 2931 μs/cm, total suspended solids 100 mg/L, biochemical oxygen demand 90 mg/L, chemical oxygen demand 250 mg/L, total phosphorus 7.9 mg/L, and total nitrogen 70 mg/L. This exerts a huge load on the biological treatment unit. Thus, this study offers an understanding and support in selecting appropriate treatment for industrial wastewater to obtain an effluent suitable in compliance with standards of the environmental quality.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.270
Teacher spread0.225 · 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