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Bio-Oil Production from Cirsium yildizianum through Pyrolysis in a Fixed-Bed Reactor

2014· article· en· W1982629705 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Applied Solution Chemistry and Modeling · 2014
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPyrolysisProduction (economics)Environmental sciencePulp and paper industryWaste managementPetroleum engineeringEngineeringEconomicsMicroeconomics

Abstract

fetched live from OpenAlex

Pyrolysis of Cirsium yildizianum samples were carried out in a fixed-bed tubular reactor with (tincal, colemanite and ulexite) and without catalyst catalyst at three different temperatures (350, 450, 550 oC) with a constant heating rate of 50 oC/min. The yields of bio-char, bio-oil and gas produced along with the compositions of the resulting bio-oils were determined by elemental, Fourier transform infrared spectroscopy (FT-IR) and Gas chromatography/ mass spectrometry (GC–MS). The effects of pyrolysis parameters including temperature and catalyst on product yields were investigated. The results indicate that both temperature and catalyst had signficant effect on conversion of Cirsium yildizianum into solid, liquid and gas products. The highest liquid (bio-oil) yield of 40.62% including aqueous phase was obtained in the presence of colemanite (10%) as catalyst at 550 oC. 79 different compounds were identified by GC-MS in bio-oils obtained at 550 oC.

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 score0.058
Threshold uncertainty score0.543

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 head0.011
GPT teacher head0.205
Teacher spread0.193 · 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