The Estimation of Hydraulic Properties from Geophysical Measurement of Subsoil Depend on Regression Equation
Bibliographic record
Abstract
This paper illustrated an establishment relationship between electrical resistivity by using electrical resistivity imaging (ERI) technique and hydraulic conductivity. The test conducted in two locations (Kampung Semerbok, Rembau and Felda Bukit Rokan Utara, Gemencheh) in Malaysia. Schlumberger array configuration was adopted by using ABEM SAS 4000 with eighty-one (81) electrodes for first site and forty-one (14) electrodes for second site. The total length of resistivity survey line was 400 m and 200 m for site one and two respectively. Statistical analysis based on regression equation was involved to find the relationship between hydraulic conductivity and resistivity. This result was compared with the hydraulic conductivity obtained from pumping tests for the well which is located within the resistivity survey line range. This study showed a good relationship between resistivity and hydraulic conductivity and can be used as preliminary tool to assess subsurface zone with non- invasive non-destructive for the soil with reducing time and cost.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".