Bibliographic record
Abstract
1. CONTENTS (1) RESEARCH OBJECTIVES The purpose of this study is to the Macroscopic Analyses of Domestic House Market evaluate the Real Estate Economic and Domestic Howse Market in Korea. (2) RESEARCH METHOD Through the former research reviews, the direction and the flow of study were set up and selected the list of theory for reviewing. This study was focused on house prices and Governmental house policies analysis. This study used to the Macroscopic Analyses (3) RESEARCH FINDINGS In the results of this rearch, the most important problem of the house price is not analysed in detail. 2. RESULTS There are a lot of doubts on how much governmental house policies are effective, because the government intervenes in markets everytime house price is instable Most researchers judge effects on the price, dividing policies in go those before as well as after enforcement, guess police effects, constructing modes on the target at measured indexes, and put into practical use the materials such as GDP, classifying them with quarter years. But, the house price is not analysed in detail. This thesis aims at finding suggestion and offering proper direction headed for in the future under the mentioned subjects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.038 | 0.003 |
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".