Characteristics of organic material inputs affect soil microbial <scp> NO <sub>3</sub> </scp> <sup>−</sup> immobilization rates calculated using different methods
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Microbial immobilization of nitrate (NO 3 − ) is considered to be an important process in reducing NO 3 − accumulation and regulating nitrogen (N) retention capacity in soils. Accurately quantifying the rate of microbial NO 3 − immobilization is, therefore, necessary to predict its role in lowering NO 3 − accumulation in soils. We compared microbial NO 3 − immobilization rates using a 15 NO 3 − labelling technique in three different ways: (a) 15 N pool dilution, (b) organic 15 N recovery and (c) microbial biomass 15 N recovery, in a nitrate‐rich upland soil with and without amendment with organic materials with differing carbon‐to‐nitrogen ratios (C/N). The three methods generated similar NO 3 − immobilization rates, except when the soil was amended with easily decomposable organic materials (glucose and sucrose). We also developed a microbial NO 3 − immobilization‐specific quality index that incorporates the C/N ratio, lignin, cellulose and hemicellulose contents and pH for slowly decomposing organic materials (plant residues). This study provides direct empirical evidence that the results of different methods for calculating soil microbial NO 3 − immobilization rates are affected by the characteristics of organic materials added to the soil. Highlights Three methods for estimating microbial NO 3 − immobilization were compared The methods generated similar NO 3 − immobilization rates when amended with plant residues Higher NO 3 − immobilization when measured with 15 N dilution with readily available C input A microbial NO 3 − immobilization‐specific index for plant residues was developed
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it