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Record W2037416583 · doi:10.5539/mas.v2n6p115

Sorption Kinetic Studies of Medical Grade Activated Carbon Prepared from Papaya Seeds

2008· article· en· W2037416583 on OpenAlexvenueno aff
Mei P. Lee

Bibliographic record

VenueModern Applied Science · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsnot available
FundersUniversiti Malaysia Sabah
KeywordsSorptionActivated carbonMethylene blueAdsorptionMuffle furnaceKineticsAqueous solutionChemistryNuclear chemistryLangmuir adsorption modelKinetic energyCarbon fibersMaterials scienceOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The aim of this investigation was to determine the adsorption behavior and kinetics of methylene blue in aqueous solution on activated carbons prepared from papaya seeds by way of the two stage activation method in self-generated atmosphere using a muffle furnace. The optimised activated carbon, AK7, had a sorption kinetic that complied with the pseudo-second order kinetics and was fitted well to Langmuir isotherm model. The highest adsorption capacity of 97.09 mg g-1was obtained when the samples (AK7) were subjected to activation temperature of 500oC for 60 minutes with the percentage of methylene blue removal efficiency of 99.5%.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.983

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 studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.038
GPT teacher head0.275
Teacher spread0.238 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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