Accurate and Precise Measurement of Organic Carbon Content in Carbonate-Rich Soils
Bibliographic record
Abstract
Accurate measurement of soil organic carbon (SOC) is dependent on precise and fast methods for the separation of organic and inorganic carbon. The widely used methods involving thermal decomposition of soil samples at a specific temperature in an automated carbon (C) analyzer are susceptible to interference by carbonates and overestimation of organic C, and thus removal of carbonates by acid pretreatment of samples is recommended. Two carbonate-removal pretreatments including hydrochloric (HCl) acid addition and HCl fumigation are compared using the calcium carbonate (CaCO3) standard and soil samples of varying SOC contents. Both pretreatment methods provided similar measurements of organic C, indicating that both methods are efficient in removal of carbonates present in the soil. However, the HCl fumigation method exhibited greater accuracy and precision compared to the HCl addition method. Hence, SOC measurement procedure involving HCl fumigation as a pretreatment for the removal of carbonates is recommended for carbonate-rich soils.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".