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Análise de copolímeros de etileno alfa-olefinas por meio de técnicas de fracionamento

2000· article· pt· W2142451624 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolímeros · 2000
Typearticle
Languagept
FieldEnvironmental Science
TopicChemical Synthesis and Characterization
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

Este trabalho apresenta a avaliação da heterogeneidade de resinas comerciais de copolímeros de etileno-1-buteno, produzidas por diferentes processos com catalisadores Ziegler-Natta e de resinas de copolímeros de etileno-1-hexeno sintetizadas em laboratório com catalisadores metalocênicos suportados e em solução. Para fazer a avaliação da heterogeneidade foram empregadas técnicas de fracionamento por extração com diferentes solventes e temperaturas e fracionamento térmico por DSC. As frações obtidas foram caracterizadas por 13C-NMR, FTIR, SEC e DSC. Como esperado, foi confirmada uma maior heterogeneidade das resinas sintetizadas com catalisador Ziegler-Natta quando comparadas às resinas metalocênicas. A resina obtida com catalisador Ziegler-Natta, produzida pelo processo Union Carbide (UCC), apresenta uma incorporação mais homogênea de comonômero do que o processo Spherilene. A resina obtida com catalisador metalocênico homogêneo permite maior incorporação de comonômero resultando em uma maior heterogeneidade no tamanho das cadeias comparada com a obtida com catalisador metalocênico suportado.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.400
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0610.003

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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