Document No. TR-95-5499-02 29 November 1995
Bibliographic record
Abstract
This report describes and motivates the framework to be used in analysing Ada95 [0] for use on critical applications. The report responds to the first deliverable of the Government of Canada contract identified as "Ada9X Trustworthiness Study" and PWGSC (Public Works-Government Services Canada) File Number W2207-5-RC02/01-SV. This contract is issued on behalf of the Department of National Defence, Chief of Research and Development (CRAD), hereafter called the Technical Authority. This work is being done in concert with the Safety and Security Rapporteur Group of the International Ada Working Group, ISO-IEC/JTC1/SC22/WG9/HRG, otherwise known simply as the "HRG". Members of this group are contributing directly to this document and future documents, and are actively reviewing drafts of all documents. It is our intent, and has been agreed by the Technical Authority, that the documents produced under this contract be used by the HRG in the development of Trusted Ada95 subsets. This report consists of seven sections, references and two appendices: . Introduction . Background . Underlying Principles and Themes . Approach . Programming Language Issues . Framework . Conclusions . References . Appendices ORA Canada/Maurya Software 29 November, 1995 Ada95 Trustworthiness Study Framework Document TR-95-5499-02
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.322 | 0.388 |
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; the direct Gemma label and the distilled Codex classifier 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".