Synthesis of quality control procedures in the conduct of precision testing of standard soil mixes
Bibliographic record
Abstract
Geotechnical index property test inputs are very important in foundation design in terms of soil classification and settlement calculations. It is therefore crucial to have accurate and reliable parameters for more reliable and safer foundation design. In this research, Six Sigma and House of Quality were utilized and incorporated in the inter laboratory study (ILS) precision testing of standard soil mixes of Ottawa sand, Bentonite and manufactured sand. Specific Gravity tests, Sieve Analysis, Liquid Limit Test and Plastic Limit Test were conducted by Six (6) participating laboratories, including the Department of Public Works and Highways (DPWH), Bureau of Research and Standards laboratory. The conduct of the ILS shows that for the soil tests, only sieve analysis produced good repeatability and reproducibility values. Both Specific Gravity Test and Liquid Limit and Plastic Limit Tests showed high r and R values. To rectify this, the observed probable sources of errors during the conduct of the ILS were identified and quality control measures were employed for a retest conducted in a single laboratory. Retest results fell within the acceptable range of two results specifications of ASTM. Therefore, the quality control measures and procedures employed in the retest and ASTM precision statements were recommended to be followed for the proposed diagnostic testing for the DPWH Private Laboratory Accreditation and for the proposed accreditation of laboratory technicians.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".