Effect analysis of using tall oil pitch (TOP) to partially extend bitumen in asphalt pavements: comparison of different TOPs
Bibliographic record
Abstract
Tall oil pitch (TOP) is widely available as a by-product, but not sufficiently valorized and has potential as a bitumen extender. In this research, three types of TOP were used to prepare bio-extended binders of two grades based on the penetration and softening point of target neat binders. The chemical, rheological, and fatigue behaviour of bio-based binders and reference binders were investigated and compared. The optimum TOP contents were inversely determined based on penetration and softening point fitting equations. New C = O and C–O–C stretching can be found in bio-based binders. Different TOPs can significantly increase the viscous response of asphalt binders, resulting in better low-temperature properties but reduced high-temperature properties. A high amount of TOP can significantly reduce fatigue resistance. This work reveals that TOP can work as extenders for bitumen, but the performance of bio-based binders is affected by the TOP type and amount.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".