The Integrated Deconvolution Estimation Model: A Parameter Estimation Method for Ethylene/<i>α</i>‐Olefin Copolymers Made with Multiple‐Site Catalysts
Bibliographic record
Abstract
Abstract The integrated deconvolution estimation model (IDEM) to estimate the microstructural parameters of polyolefins made with multiple‐site catalysts is described. IDEM estimates ethylene/α‐olefin reactivity ratios for each site type in two‐steps. In the first step, the MWD of the whole copolymer is deconvoluted into several Flory's most probable distributions, to determine the number of site types and the weight fraction of copolymer made on each of them. In the second estimation step, the model deconvolutes the CSLD of the copolymer into its individual components per site type, and estimates their respective reactivity ratios. This is the first time that MWD and CSLD information is integrated to estimate the reactivity ratios of polyolefins made with multiple‐site catalysts. magnified image
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".