New Regression Model for Estimating Irrigation Water Quality Index
Bibliographic record
Abstract
The common tool to evaluate the groundwater quality is so-called the Irrigation Water Quality Index (IWQI). In the present study, the IWQI model developed by Meireles is used to assess the quality of groundwater in Karbala - Najaf plateau, Iraq. The quality parameters that collected from groundwater tests of 78 wells in the study area are; EC, Na+1, Mg+2, Ca+2, Cl-1, and HCO3-1. The SPSS software program is employed to develop a non-linear regression model of the IWQI for the study area. The results show that the IWQI values for 90% of groundwater wells fall within the Severe Restriction (SR) category, which means that it’s only suitable for irrigation of high salt tolerance crops. While its remaining 10% of the wells are in the High Restriction (HR) category, and this means it is suitable for irrigation of moderate to high salt tolerance crops. The calibration and validation for the developed model presented that this model has a good estimation of the IWQI values. Due to flexible and unbiased, the current study recommends to use the proposed model to estimate the IWQI.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".