Latvian Real Estate Announcements Monitoring in 2021 Q1
Bibliographic record
Abstract
This data set represents real estate market announcements monitoring data in Latvia in first quarter of 2021 . The data was collected from online ads site ss.com. The database contains 52 thousand ads and consists of 24 groups of data (type of deal, price, characteristics and address of real estate, etc.). The data reflects the dynamics of price changes by months (at the beginning of the month) in first quarter of 2021. Monitoring continued in 2021 was started in 2018. 2018 year dataset is available in Skribans, Dr.oec. V. (Riga Technical University) (2019): Latvian Real Estate Announcements Monitoring in 2018. DANS. https://doi.org/10.17026/dans-2z3-fx28 , 2019 year data is available in Skribans, Valerijs (2019), “Latvian Real Estate Announcements Monitoring in 2019”, Mendeley Data, V1, doi: 10.17632/m7bzjsx557.1 , 2020 year data is available in Skribans, Valerijs (2020), “Latvian Real Estate Announcements Monitoring in 2020”, Mendeley Data, V1, doi: 10.17632/wrnvjfszc9.1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".