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Record W1686913351 · doi:10.18331/brj2015.1.3.5

Pyrolysis of Parinari polyandra Benth fruit shell for bio-oil production

2014· article· en· W1686913351 on OpenAlexvenueno aff
T. E. Odetoye, K. R. Onifade, Muhammad Saifullah Abu Bakar, James O. Titiloye

Bibliographic record

VenueBiofuel Research Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPyrolysisGuaiacolRaw materialChemistryPhenolAcetic acidPulp and paper industryBiomass (ecology)TolueneOrganic chemistryFood scienceAgronomyBiologyCatalysis

Abstract

fetched live from OpenAlex

Non-conventional agricultural residues such as Parinari polyandra Benth fruit shell (PPBFS) are potential sources of biomass feedstock that have not been investigated for bio oil production. In this study, PPBFS was pyrolyzed via an intermediate pyrolysis process for the production of bio oil. The bio oils were obtained using a fixed bed reactor within a temperature range of 375–550 oC and were characterized to determine their physicochemical properties. The most abundant organic compounds present were acetic acid, toluene, 2-cyclopenten-1-one, 2-furanmethanol, phenol, guaiacol and 2,6-dimethoxyphenol. The bio-oil produced at 550 oC possessed a higher quantity of desirable compounds than those produced at lower temperatures. The presence of acetic acids in the bio-oil suggested the need to upgrade the bio-oil before utilization as a fuel source.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.076
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.039
GPT teacher head0.301
Teacher spread0.262 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

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