Analysis of the quarterly evolution of the Gross Domestic Product
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gross Domestic Product is the most complex indicator of the results of a country's economy. The Gross Domestic Product expresses the concrete results obtained in the national economy and depending on its evolution, there are also possibilities for increasing consumption, domestic investment and last but not least the possibility of diversification of the national economy. The analysis of the evolution of the Gross Domestic Product was performed starting from the resources and uses that this indicator had in achieving these results. At the same time, the analysis is performed based on the raw data series, but also on the seasonally adjusted data series. In order to highlight the evolution of the Gross Domestic Product, analyzes were performed for periods of time starting with the year 2000, in order to capture the effects of the economicfinancial crisis, but then also for shorter periods of time, 2017-2019 or 2018-2020. All this was done in order to highlight the evolution over time, but also to shed light on the danger that exists in terms of the negative effect of the health crisis, coronavirus, which will certainly have negative effects. Probably if in the second quarter of 2020 we have a decrease in Gross Domestic Product of 12.3%, compared to the first quarter of 2020, it is not excluded that during the third and fourth semesters of 2020 we will also record non-compliant, inconclusive results, which may result in a double-digit reduction in Gross Domestic Product at the end of the year compared to the previous year 2019. The analysis aimed precisely at highlighting these trends and the way in which the structural analysis on different groups of factors (resources, uses and other macroeconomic indicators, inflation, unemployment, foreign direct investment, domestic investment, etc.), have on the national economy. All should have a beginning to restructure strategies to halt the macroeconomic decline and bring it into a position of stabilization and then resumption of growth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it