Structural Integrity Prognosis System Reasoning
Bibliographic record
Abstract
The purpose of the DARPA/Northrop Grumman Structural Integrity Prognosis System (SIPS) Advanced Reasoning and Adaptive Prediction methods is to provide a prompt, useful prediction of remaining fatigue life in a structural element. In order to make the current life prediction as accurate as possible, a two-stage, adaptive updating procedure has been devised for this program. Predictions are made at the outset using microstructural models of fatigue and the expected usage. These models use values of the random variables representing the inputs, and the random output from the model is described by stochastic processes from which predictions are made. At various intervals during the life of the component, the predictions are updated with any new information that may be available. The revised predictions are determined from the adaptations that modify the remaining useful life and failure distributions based on current state assessment. Furthermore, the Monte Carlo method has been replaced by a novel method in SIPS to accurately and efficiently calculate the probability distributions of the random output.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".