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Record W2131486320 · doi:10.5539/ijc.v2n1p97

Chemical Changes in 15 Year-old Cultivated Acacia Hybrid Oil-Heat Treated “at 180, 220 and 220°C”

2010· article· en· W2131486320 on OpenAlexvenueno aff
Izyan Khalid, Razak Wahab, Mahmud Sudin, Othman Sulaiman, Affendy Hassan, Roziela Hanim Alamjuri

Bibliographic record

VenueInternational Journal of Chemistry · 2010
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryAcaciaLigninHemicellulosePalm oilHorticultureChemical compositionBotanyFood scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The chemical constituents of oil-heat treated cultivated 15 years-old Acacia hybrid were investigated. The logs of A.hybrid were harvested and cut at bottom, middle and top portions and oil-heat treated using organic palm oil attemperatures of 180, 200 and 220°C for the time 30, 60 and 90 minutes. The wood samples were dried and grinded intosawdust, and air-dried again prior to the chemical analysis. Untreated samples were used as controls. The results on theanalysis of the chemical contents in the oil-treated A. hybrid shows some changes occurred when treated from 180 to220°C. The variation occurred in the chemical contents for both the sapwood and heartwood. The holocellulose contents decrease from 71.5 to 63.1% and 73.4 to 64.0% for sapwood and heartwood respectively. The cellulosecontents decreased from 47.1 to 37.7% for the sapwood and 48.9 to 38.1% for heartwood. The hemicellulose content'sincreases from 24.4 to 25.4% in the sapwood and 24.5 to 25.9% for the heartwood. Lignin contents increased 20.8 to24.0% for the sapwood and 22.4 to 24.9% in the heartwood for treatment temperature from 180 to 220°C.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2010
Admission routes1
Has abstractyes

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Same venueInternational Journal of ChemistrySame topicWood Treatment and PropertiesFrench-language works237,207