Integrated approach between pulsed thermography, near-infrared reflectography and sandwich holography for wooden panel paintings advanced monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The durability of an exterior finish is affected by the characteristics of the wood. Satisfactory finish life is usually more difficult to achieve on woods of higher density. All wood shrinks as it loses moisture and swells as it absorbs moisture, but some species are more stable than others. Species that shrink and swell the most cause more stress on paint films than woods that are more stable [1]. To this end, let us recall that a painting on wood can be considered as a layered structure: The wood support is coated with a number of superposed priming layers made from mixtures of gesso and glue. A frequent fault resulting from such a system is the formation of detached regions inside the layered structure caused by the shrinkage process of the wood support [2]. Obviously, wood deteriorates more rapidly in warm, humid regions with respect to cool or dry places [3]. The influence of wood conditions on surface coatings is a critical point that should be monitored and that depends on environmental parameters such as microclimate. To prevent and control the effects, keeping costs down, a non-destructive monitoring of wood support behavior under thermal stress is needed. In this work, an integrated approach based on traditional and innovative ( HI , PT and NIR ) techniques was conducted on a primed support of poplar wood with a complex-shape surface containing areas of artificial defects at several depths due to the influence of the support on the various layers. The obtained results could be arranged, if integrated into a multidisciplinary approach, in order to define and design the conservation of the wooden artifacts.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it