Bibliographic record
Abstract
The market for real estate portfolios in Europe will stabilise at a high level over the coming years. Numerous factors are favourably impacting supply and demand and will continue to promote extensive investment. After a short introduction covering the macroeconomic and real estate market environment, the presentation will show the development of the market of portfolio transactions in several European countries, Germany, UK, France, Sweden, Italy, Central Europe [Poland, Czech Republic, Hungary, Slovakia], pan-European transactions - including the number of transactions per year, volumes, types of vendors and purchasers, nationalities of vendors and purchasers utilisation. The analysis covers all transactions from 1997 or later ñ depending on the country - and includes transactions up to the 3rd quarter of 2006. The energy of the market is the motivation of vendors and purchasers, new financing instruments and exit strategies. These factors will be also highlighted in the presentation. After discussing all of the mentioned dynamic features, we are able to give an informative picture about the future development of the market of portfolio transactions within Europe. The presentation is based on the new report published by Sireo Research in February 2007: ìSireo Research 2007 ñ Portfolio transactions in Europeî.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".