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Record W7115060445 · doi:10.21467/proceedings.7.8.10

Defluoridation of Water Using Low Cost Bioadsorbents

2025· article· W7115060445 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

VenueAIJR Proceedings · 2025
Typearticle
Language
FieldEnvironmental Science
TopicFluoride Effects and Removal
Canadian institutionsBishop's University
Fundersnot available
KeywordsBambooBamboo shootShell (structure)AdsorptionFluorideShootCarbon fibers

Abstract

fetched live from OpenAlex

To meet drinking water standards, fluoride levels must be kept below 1 mg/L to prevent fluorosis. This study evaluates low-cost bioadsorbents—cashew shell powder, coconut shell powder, coconut shell crystal, and hydrothermally treated bamboo shoot powder—using batch adsorption at pH 4.4–4.9 and contact times of 1.5–3 hours. 3.5 g coconut shell powder and a mixture of 1.5 g coconut shell powder and 1.5g of cashew shell powder achieved 10 % removal, reducing fluoride from 10 ppm to 9 ppm. Both 2 g coconut shell crystal with 1 g cashew shell powder and bamboo shoot powder dosages of 2–6 g achieved 30 % removal (10 ppm to 7 ppm), while higher bamboo shoot dosages (8–10 g) showed lower efficiency due to supersaturation. The crystal form of coconut shell and bamboo shoot carbon are the most effective adsorbents, and it was found that dosage, pH, and contact time influence the Deflouridation efficiency. These bioadsorbents can be used for community level defluoridation using affordable, locally available materials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.245
Teacher spread0.237 · 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