DEUTERIUM AS A NOVEL TRACER FOR DETERMINING MOISTURE SOURCES IN BUILDING SYSTEMS
Bibliographic record
Abstract
Many current problems in moisture-related deterioration of housing are found in the building envelope. Components such as interior surfaces, siding, millwork, sheathing, and framing are damaged due to excessive moisture accumulation, which leads to potential biodeterioration (mold and decay). The monetary and health implications of such widespread failures are severely impacting the housing industry. In certain individual cases of wood wetting, the source of liquid water is readily determined: typically, a failure of external sealing allows direct ingress of precipitation into the wall system. There is, however, still a debate on the role of subsequent moisture movement or condensation (from water vapor movement to a cool surface) in wall and roofing system failures. Here we show that deuterium-labeled water introduced into wood through either liquid or vapor phase can be recovered via distillation or mechanical expression. The use of deuterium as a moisture tracer can assist in determining the origin of moisture (particularly through the vapor phase transition), provide insight into current recommended practices for moisture control in buildings, and assess the application of current moisture modeling on existing moisture failures.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".