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Record W4399277268

INFLUENCE OF THE SIZE OF METHYLENE SPACERS ON THE THERMAL BEHAVIOR OF SEVERAL ALIPHATIC-AROMATIC POLYESTERS

2014· article· en· W4399277268 on OpenAlexaff
Natalia Hurduc, Gabriela Lisă, Violeta Toader

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsPolyesterMethyleneChemistryPolymer sciencePolymer chemistryOrganic chemistryMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Polyesters have a wide range of technical applications and therefore their processing is of the utmost importance. Since polyesters are usually processed by melting, their thermal stability is an extremely important characteristic for the exact determination of the operational parameters. The thermal analysis was carried out using a MOM-Budapest derivatograph at the 10 C/min heating speed, aluminum oxide the reference material, and the air conditions were static. The study lead to conclusions on the thermal stability and degradation mechanism depending on the number of methylene groups in the spacer. Thermal stability is supported by the increase in the number of methylene groups in the spacer. The degradation mechanism is complex through successive reactions. The spacer size influences the nature of the micromolecules formed by spacer fragmenting and by the number of carbon atoms, respectively.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.106
GPT teacher head0.459
Teacher spread0.354 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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