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Record W7030595805

Molecular growth, aerosol formation and pyrolytic carbon deposition during the pyrolysis of ethane at high conversion

2000· other· en· W7030595805 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2000
Typeother
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsnot available
Fundersnot available
KeywordsPyrolytic carbonPyrolysisAerosolDeposition (geology)Carbon fibersHydrocarbonCombustionChemical vapor deposition
DOInot available

Abstract

fetched live from OpenAlex

When hydrocarbons are placed in a high temperature environment, energy is introduced into the individual molecules. Redistribution of this energy often results in the "cracking" of C-C bonds, the formation of radicals, and a general reduction in the size of the molecules. A small fraction of these molecules react with one another, growing into large, stable species including carbon. The accumulation of carbon on heated reactor surfaces when in the presence of hydrocarbons is a serious industrial problem. The deposits are complicated, generally containing a number of distinct, carbon-rich materials. Available evidence suggests pyrolytic carbon deposits directly on the reactor surface as a small hydrocarbon or that polymerization and condensation reactions may play an important role. However, there is insufficient evidence to distinguish which mechanisms dominate. This thesis examined the role of molecular growth and aerosol formation in carbon formation during the pyrolysis of ethane.

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)0.000
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.004
GPT teacher head0.188
Teacher spread0.185 · 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
Published2000
Admission routes1
Has abstractno

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