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Record W2131854030 · doi:10.5539/jsd.v1n1p31

Zinc Bioremoval from Wastewater of Rubber Glove Industry

2009· article· en· W2131854030 on OpenAlex
Azizah Abu-Bakar, Rakmi Abd-Rahman, Abu Bakar Mohamad, Abdul Amir H. Kadhum, Siti Rozaimah Sheikh Abdullah

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

VenueJournal of Sustainable Development · 2009
Typearticle
Languageen
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
FundersMinisterio de Ciencia, Tecnología y Medio Ambiente
KeywordsEffluentZincPulp and paper industryAnaerobic digestionWastewaterHeavy metalsChemistryHydraulic retention timeNatural rubberMetal ions in aqueous solutionWaste managementEnvironmental scienceMetalEnvironmental chemistryEnvironmental engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Conventional physicochemical processes for removing heavy metals from industrial effluents are high in chemical usage and produce large amounts of chemical sludges, which in turn needs secured disposal. Biological processes to overcome these problems have been developed for treating wastewaters containing heavy metals. The bioremoval and biorecovery of zinc ions from rubber glove mill effluent on a sequencing batch biofilm reactor (SBBR) was studied. Without adding any precipitant, the processes could achieve Zn and COD removal of 40-60% and 50-70% respectively. In order to recover the metal, the sludge was digested in an anaerobic digestion reactor. This study revealed that anaerobic digestion with longer hydraulic retention time could increase the recovery of heavy metals. This recovery prevents metal discharge to the environment and conserves resources.

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 score0.172
Threshold uncertainty score0.365

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 communication0.0000.000
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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