Ultrasonic Waves and Strength Reduction Indexes for the Assessment of the Advancement of Deterioration Processes in Travertines from Pamukkale and Hierapolis (Turkey)
Bibliographic record
Abstract
Abstract In constructions, the usefulness of modern technical diagnostics of stone as a raw material requires predicting the effects of long-term environmental impact of its qualities and geomechanical properties. The paper presents geomechanical research enabling presentation of the factors for strength loss of the stone and forecasting the rate of development of destructive phenomena on the stone structure on a long-time basis. As research material Turkish travertines were selected from the Denizli-Kaklık Basin (Pamukkale and Hierapolis quarries), which have been commonly used for centuries in global architecture. The rock material was subjected to testing of the impact of various environmental factors, as well as European standards recommended by the author of the research program. Their resistance to the crystallization of salts from aqueous solutions and the effects of SO 2 , as well as the effect of frost and high temperatures are presented. The studies allowed establishing the following quantitative indicators: the ultrasonic waves index (I Vp ) and the strength reduction index (I Rc ). Reflections on the assessment of deterioration effects indicate that the most active factors decreasing travertine resistance in the aging process include frost and sulphur dioxide (SO 2 ). Their negative influence is particularly intense when the stone material is already strongly weathered.
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 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 | 0.002 | 0.001 |
| 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".