Investigating the evolution of the chemical nature of SOM through stabilization thanks to long term field experiments and state-of-the-art synchrotron-based NEXAFS spectroscopy
Bibliographic record
Abstract
Though it is of crucial importance in order to better understand carbon stabilization in soils, the chemical nature of stable soil organic matter (SOM) is poorly characterized. This is explained by two major difficulties: (1) there is still no successful experimental way to isolate the pool of SOM that has a pluri-decennial residence time and (2) SOM with high residence time is often associated to minerals, which complicates its characterization.In this work, we overcame these two major difficulties by characterizing samples from long term bare fallow (LTBF) experiments using the state of the art synchrotron basedNEXAFS spectroscopy (Canadian Light Source, Saskatoon, Canada). Firstly, LTBF experiments offer a unique opportunity to study stable SOM, as without carbon inputs and with continuing biodegradation and mineralization, SOM becomes progressively enriched in its most stable components. Secondly, NEXAFS technique allows the characterization of Carbon speciation with no sample pre-treatments and no noise induced by the mineral part of the samples. In this work, the fluorescence emission spectra at the Carbon K edge threshold (280 eV) were measured for samples taken up at the initiation of 5 different european LTBF experiments and several decades later. Results show that differences in chemical composition between different dates are subtle but significant and spectra are highly reproducible between field replicates. More advanced data treatment is ongoing and will be presented at SOM6
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".