General electric CF34-10 icing certification test plan 2002/2003 project implementation plan
Bibliographic record
Abstract
The National Research Council Canada (NRC) has entered into a contract to perform, with the support of General Electric Aircraft Engines (GEAE), icing certification tests on a General Electric CF34-10 gas turbine. The tests will be conducted in an icing certification facility located in test cell No. 4 of building M-7 within the Structures, Materials and Propulsion Laboratory of the Institute for Aerospace Research. This project, will commence on December 1, 2002 and end on March 31, 2003. The total estimated cost to perform the project is approximately $1.6 million USD as per NRC’s proposal of June 16, 2002 based on a 50 hour icing test program. This project implementation plan (PIP) is a NRC/IAR internal document and was created for the purposes of facilitating the execution of the project. This document defines the scope statement, Work Breakdown Structure, monitor/control procedures, and reporting procedures to be followed throughout the project life cycle. The primary aim of this project is to perform icing certification tests to meet the test requirements outlined in the GEAE Statement of Work issued June 27, 2002. NRC will conduct the tests with assistance from GEAE. It is anticipated that the test matrix outlined in a prliminary CF34-10 Far 33.68 Icing Test Matrix can be completed within the four month time frame. The deliverables of this project will include those outlined in the GEAE Statement of Work. This section provides details on project organization, reporting structure, and detailed objectives of the major tasks.
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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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.013 |
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".