TREND: Federal Reserve Board. Currency Exchange Rates: Exchange Rates | Convert From: United States | Convert To: Canada, 01/04/1971 - 11/10/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 014-003-001
Bibliographic record
Abstract
Federal Reserve Board. Currency Exchange Rates: Exchange Rates | Convert From: United States | Convert To: Canada, 01/04/1971 - 11/10/2016. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 014-003-001 Dataset: The price of the currency of one nation in terms of the currency of another nation. Exchange rates are certified by the Federal Reserve Bank of New York for customs purposes as required by section 522 of the amended Tariff Act of 1930. These rates are also those required by the SEC for the integrated disclosure system for foreign private issuers. The information is based on data collected by the Federal Reserve Bank of New York from a sample of market participants. http://www.federalreserve.gov/releases/h10/Hist/ Category: Banking, Finance, and Insurance Subject: Money, Exchange Rates Source: Federal Reserve Board The Federal Reserve System, established by the Federal Reserve Act of 1913, serves as the central bank of the United States. The Board of Governors (Federal Reserve Board) determines general monetary, credit, and operating policies for the System as a whole and formulates the rules and regulations necessary to carry out the purposes of the Federal Reserve Act. http://www.federalreserve.gov/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.073 | 0.007 |
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".