Characterization of an amphimull under Mediterranean evergreen oak forest (<i>Quercus ilex</i>): micromorphological and biodynamic descriptions
Bibliographic record
Abstract
The relationships between microorganisms and microfauna were studied in an evergreen oak ( Quercus ilex L.) forest floor located in a French Mediterranean region characterized by hot and dry summers. The soil was a brown fersialitic soil with an amphimull, i.e., a mull with a thick litter. A micromorphological study of both litter and organomineral layers was used to observe relationships between white-rot fungi and fauna, such as oribatids, millipedes, enchytraeids, and earthworms. Microbiological properties of the litter and physicochemical properties of the soil were analysed. Enchytraeids comminute the faeces of other animals, whereas earthworms form aggregates. These two opposite actions probably modify aeration and water movements in deeper layers. Brown leaves and animal faeces constitute a nutritional substrate for white-rot fungi and other animals. Inside degraded cells of rootlets and bleached leaves, fungi form calcium oxalate crystals because the absorbent complex is saturated by an excess of calcium. Enzymes such as laccases, manganese peroxidases, cellulases, or xylanases were detected in the litter at significant levels. The high activity values of phosphatases in the litter could reflect a deficiency in available phosphorus. This deficiency could partly explain a low rate of litter degradation and the presence of an OH sublayer.
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 | 0.001 | 0.000 |
| 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 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".