Bibliographic record
Abstract
On behalf of the Organizing Committee and myself, it is my pleasure to welcome you to the 27th Symposium on Hydraulic Machinery and Systems. We are glad to welcome you in Montreal, Canada, in late September, just as the city welcomes the fall season and the trees start to show their nice colors. The Symposium will take place at the Hotel Omni Mont-Royal, located in the heart of the city. Participants will then have the opportunity to discover the many charms of Montreal, a rich blend between European and American cultures with diverse culinary offers and its legendary hospitality, nightlife and unique attractions. But other than the charm of Montreal, why are we holding it in Canada? · Canada is a world leader in hydropower production, with an installed capacity of over 70,000 megawatts (MW) and an annual average production of 350 terawatt-hours (TWh). · Thus, Canada is one of the world's largest producers of clean, renewable hydroelectric power. · Hydropower accounts for 97% of Canada's renewable electricity generation and nearly 13% of the world-wide production of hydropower, but with 0.5% of the world population. · Approximately 60% of the electricity generated in Canada in 2008 came from hydroelectric power plants. And there is the potential to more than double the hydroelectric capacity in Canada. Our Organizing Committee was formed in November 2011 and has undertaken a number of important steps to ensure that this event will be a success. We see this event as a very important one to help create personal networks and transfer knowledge to the younger generation of scientists. Bienvenue at our 2014 ‘‘rendez-vous’’ . Normand Désy Canadian Representative IAHR Executive Committee
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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.116 | 0.088 |
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".