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Record W2001802334 · doi:10.1504/ijep.2008.018414

Sequestering of heavy metal ions from aqueous solutions by using a lignocellulosic material

2008· article· en· W2001802334 on OpenAlex
Rajeev Chandraghatgi, Peter Englezos

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

VenueInternational Journal of Environment and Pollution · 2008
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPulp (tooth)Aqueous solutionMetal ions in aqueous solutionKraft processKraft paperChemistryMetalPulp and paper industryEnvironmental chemistryInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The ability of Brown Stock Washer (BSW) unbleached kraft pulp and Chemi-Thermo-Mechanical Pulp (CTMP) to sequester heavy metals was studied. The BSW pulp is chemically produced while the CTM one is produced by mechanical treatment aided by some chemicals. The two pulps were rendered in their protonated form and then equilibrated with two aqueous solutions of metals. One was ocean water and the other was a laboratory prepared solution of metal ions. Both pulps were able to remove metal ions from the solution in a one-stage procedure. The overall metal removal efficiency of CTMP was in general greater than that of the BSW pulp for the low concentration metals.

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 score0.003
Threshold uncertainty score0.323

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 head0.016
GPT teacher head0.200
Teacher spread0.184 · 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