TREND: Exchange Data International. Worldwide Stock Market Prices - Major Exchanges: Stock Daily Close - Adjusted Prices | Exchange Symbol: XBER | Exchange Name: Berlin Stock Exchange | Stock Symbol: SHA, 10/09/2015 - 07/08/2020. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 090-002-002
Bibliographic record
Abstract
Exchange Data International. Worldwide Stock Market Prices - Major Exchanges: Stock Daily Close - Adjusted Prices | Exchange Symbol: XBER | Exchange Name: Berlin Stock Exchange | Stock Symbol: SHA, 10/09/2015 - 07/08/2020. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 090-002-002 Dataset: Reports closing stock price for companies listed on major global exchanges. Close refers to the price of the last transaction for a given stock at the end of the reference day. Adjusted figures reflect the price/volume of a stock with adjustments due to corporate actions applied. Adjusted prices are calculated by Quandl. This dataset provides historical prices for equities trading on five non-US stock exchanges (Berlin, Frankfurt, Hong Kong, London, and Toronto stock exchanges). Stock daily open, close, high, and low prices, and volume are reported. Historical depth of the time series varies by exchange and equity. See the technical documentation for detail. Prices are displayed in the local currency of the exchange. https://www.quandl.com/publishers/EDI Category: Banking, Finance, and Insurance Subject: Equities, Stock Markets, Stocks, Publicly Traded Companies, Stock Prices Source: Exchange Data International Exchange Data International (EDI) distributes professional grade financial data covering all major markets. Exchange Data International is one of the world's leading providers of professional grade financial data. https://www.exchange-data.com/
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.096 | 0.154 |
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".