Proceedings of The South African Sugar Technologists ' Association- June 1994 ELECTROMAGNETIC INDUCTION AS A TECHNIQUE FOR DIAGNOSING AND MAPPING SOIL SALINITY
Bibliographic record
Abstract
Conventional methods of measuring salinity involve soil sampling with an auger followed by analysis of a water extract ofthe sample in the laboratory. This procedure is slow, laborious and expensive. The EM-38 electromagnetic induction soil conductivity sensor of Geonics Ltd (Canada) has been developed to facilitate rapid field measurements ofsoil salinity. It responds to the electrical conductivity (EC) of the bulk soil, and this is influenced by the salinity level as well as the water content. The depth of influence of the sensor is approximately 1,5 m. Calibration equations presented allow estimation of the EC of the saturation extract for the upper 1,2 m soil depth for various categories oftexture and water status. Soil salinity maps for a study area at the La Mercy farm demonstrate the utility ofthe sensor for salinity mapping.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.070 | 0.019 |
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".