Murs d'habitations à haute performance au nord du 60e parallèle : Série de séminaires Regard 2007 sur la science du bâtiment par l'IRC-CNRC ; Recherche au CNRC sur la formation de moisissures dans les bâtiments ; Demande de renseignements : propriétés des matériaux
Bibliographic record
Abstract
NRC-IRC is conducting a study on the performance of wall assemblies appropriate for the particular conditions prevailing in regions North of the 60º parallel. Several research reports are available and can be downloaded at the website http://www.nrc-cnrc.gc.ca/eng/projects/irc/climate-extremes.html.NRC-IRC Building Science Insight 2007 Seminar Series entitled Fire Safety Research for Better Building Design will start in the fall 2007.NRC-IRC researchers have initiated a five-year mould research project focusing on the following areas: Mould-detection techniques, prediction of potential of mould growth on building materials and components and corrective methods.NRC-IRC has developed a database of building material heat and mass transfer properties, and it is integrated to NRC hygIRC 1D modeling software available at http://www.nrc-cnrc.gc.ca/eng/projects/irc/hygirc.html
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".