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Record W2022032648 · doi:10.1002/ceat.201000400

Thermogravimetry‐FTIR Analysis of Pyrolysis of Pyrolytic Lignin Extracted from Bio‐Oil

2012· article· en· W2022032648 on OpenAlex
Xiaoxiang Jiang, Naoko Ellis, Dekui Shen, Jianchun Jiang, Wei Dai, Z. Zhong

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

VenueChemical Engineering & Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPyrolytic carbonLigninPyrolysisFourier transform infrared spectroscopyThermogravimetryChemistryExtraction (chemistry)Thermal stabilityNuclear chemistryMaterials scienceChemical engineeringAnalytical Chemistry (journal)Organic chemistryInorganic chemistry

Abstract

fetched live from OpenAlex

Abstract Pyrolytic lignin is attributed to the instability of bio‐oil but is a potential chemical material. To improve the stability and increase the economic viability of bio‐oil, high‐ and low‐molecular‐mass pyrolytic lignin (HMM and LMM) were obtained using solvent extraction. The microstructure of pyrolytic lignin was examined by Fourier transform infrared spectrometry (FTIR). The dissimilar absorption intensities indicated the different content of corresponding functional groups in HMM and LMM. The pyrolysis behavior of HMM and LMM was studied by thermogravimetry coupled with FTIR. Obviously pyrolytic lignin undergoes three weight loss stages.

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 categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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