Evaluating Minnesota Crack Sealants by Modified Bending Beam Rheometer Procedure
Bibliographic record
Abstract
Due to poor performance of many of the crack sealing projects in Minnesota, research is being conducted to determine methods of improving Minnesota’s crack sealing program. The current method for the selection of crack sealants is by specifying different types of sealants satisfying the ASTM D 6690 specification. Unfortunately the ASTM specification doesn't predict expected field performance for Minnesota’s climate. Minnesota Department of Transportation (Mn/DOT) performed an evaluation of five hot-pour crack sealants that were developed for Minnesota’s climate. The evaluation used the modified Bending Beam Rheometer (BBR) method developed by the U.S.- Canada Crack Sealant Consortium and determined that a state department of transportation (DOT) asphalt binder testing laboratory can successfully test crack sealants using the modified BBR. The Mn/DOT laboratory staff was able to use creep stiffness, creep m-value and steady-state creep rate tests to rank the sealants by expected field performance. The BBR tests showed differences between low modulus crack sealants (ASTM Type IV) and showed that some ASTM Type II sealants may perform as well as some low modulus products. The findings indicate that once the U.S.- Canada Crack Sealant Consortium have validated the sealant BBR performance criteria, the low temperature performance of crack sealants may be estimated better than with the current ASTM D 6690 tests. This procedure will be extremely valuable in grading sealants by low pavement temperature, improving the crack sealant selection process and can be used as an evaluation tool for new products.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".