Fractography analysis into low-C steel undergone through various destructive mechanical tests
Bibliographic record
Abstract
Abstract The present work deals with a critical fractographic analysis into low carbon (0.18%-C) steel samples which were used for three different mechanical tests: tensile test; shear test; and toughness test. These mechanical tests were performed in standard sized specimens as recommended by ASTM. In each category of test, there were two different specimens with different physical states according to heat treated conditions. First specimen was in ‘as received’ condition and another was annealed. For annealing, sample was first heated up to austenitic temperature and inserted inside the sand for slow rate of cooling. As these two categories of samples were undergone through destructive tests, the variation in fracture behaviour of the samples was analysed by FESEM, XRD. A significant variation in fractographic images could be observed in different heat-treated samples. Micro-pores, dimples, cleavage facet, peaks, valleys, and cave formation were observed in the samples.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".