QUAND LES IMMEUBLES DE GRANDE HAUTEUR SONT EN BOIS - WHEN HIGH RISE BUILDINGS ARE MADE OF WOOD
Bibliographic record
Abstract
In 2016, the “Earth Overshoot Day” landed on the 8th August. This day represents the time of year from which human demand exceeds the earth's ability to regenerate its resources. The construction sector produces more than 70% of waste in France. Faced with this alarming observation, the methods of construction must become more virtuous. Wood, which is the only fully renewable building material, must regain a prominent place in the building industry. Its qualities, in particular, its lightness, will make it possible to propose solutions to urbanization problems by increasing heights. Its reduced weight will allow building implementation on more constrained sites. The speed of construction that wood can offer, can reduce noise and the carbon footprint. The BIM tool, already implemented within setec tpi, finds here its full usefulness with the prefabrication of wood. In France, the Wood Industries Plan, carried out by ADIVbois, envisages the construction of several high-rise wooden buildings (up to 15 storeys high). These demonstrators will have to give a new dynamic to the French wood industry and allow the development of engineered wood from local species. Similar initiatives have taken place in Canada and the USA. Some European countries such as the Scandinavian countries (14 storeys built in Norway) and Austria, have more favorable circumstances and highly competitive wood industries. France wants to catch up, thanks in particular to its currently under-exploited forest potential. Setec tpi has been appointed by ADIVbois to manage the Structures workshop of the technical commission. It has accumulated knowledge, and extended its expertise in high-rise buildings using wood material. A guide for the design of high-rise wooden buildings has been prepared for future designers. The various studies and case studies have highlighted critical points to initiate research. The notions of damping, creep, stiffness of connections will have to be mastered in order to reach new height records
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".