Analyses of artificial morel soil bacterial community structure and mineral element contents in ascocarp and the cultivated soil
Bibliographic record
Abstract
This study explored the differences among various artificial morel cultivations as well as the factors that influence these differences, including soil bacterial community structure, yield, and mineral element contents of ascocarp and the cultivated soil. High-throughput sequencing results revealed that the dominant bacterial phyla in all the samples, including Proteobacteria, Acidobacteria, Chloroflexi, Bacteroides, and Gemmatimonadetes, were found not only in morel soils (experimental group) but also in wheat soil (control group); the highest richness and diversity in the soil bacteria were observed during the primordial differentiation stage. The M6 group exhibited the highest yield (271.8 g/m 2 ) and had an unexpectedly high proportion of Pseudomonas (25.30%) during the primordial differentiation stage, which was 1.77∼194.62 times more than the proportion of Pseudomonas in other samples. Pseudomonas may influence the growth of morel. The mineral element contents of the different soil groups and the ascocarp were determined by electrothermal digestion and inductively coupled plasma mass spectrometry. The results revealed that morel had high enrichment effects on phosphorus (P, bioconcentration factor = 16.83), potassium (K, 2.18), boron (B, 1.47), zinc (Zn, 1.36), copper (Cu, 1.15), and selenium (Se, 2.27). P levels were the highest followed by Se and K, and the mineral element contents in ascocarp were positively correlated with the soil element contents.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".