CNA's Integrated Ship Database, Fourth Quarter 2011 Update
Bibliographic record
Abstract
Abstract : In this CNA Interactive Software document, we present the update of our Integrated Ship Database (ISDB) for the third quarter of calendar year 2012. In this version of the ISDB, as in the previous ones, we bring together data on naval ships from several different online government sources into a single combined database tool. The ISDB makes ship data readily accessible for analysis and reporting. With the database, you can see the makeup of the Navy's Battleforce. You can find where ships are in their life cycle: authorized by Congress, under construction, in commission/in service, in reserve, leased or loaned, stricken from the Register, or disposed. This work is being conducted as part of CNA's Historic Fleet Employment Database Project, sponsored by the Deputy Chief of Naval Operations for Operations, Plans, and Strategy (N3/N5). Since our initial version in 2005, we have published 26 quarterly updates. They are all available online on the Integrated Ship Database page of CNA's website: www.cna.org. In the first section of this document, we present an overview of the ISDB. We tell you where to find the database online and how to access it. Then we show how the Microsoft Excel database file is organized according to worksheet tabs for documentation, database navigation, data tables, and pivot tables for display and analysis. If you are looking for details, please refer to the original 2005 user's manual and to the fourth quarter 2011 update. In addition, the documentation of the second quarter 2012 update discusses the changes we made due to the Military Sealift Command's (MSC) organizational realignment of 2012. After the overview, we discuss changes in the database because of modifications to the Naval Vessel Register (NVR), the MSC Ship Inventory, and the Maritime Administration's (MARAD) National Defense Reserve Fleet (NDRF) Inventory between July 1 and September 30, 2012. Finally, we present ship counts and inventory summaries as of September 30, 2012.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".