Gall inducing arthropods from a seasonally dry tropical forest in Serra do Cipó, Brazil
Bibliographic record
Abstract
Highly diverse forms of galling arthropods can be identified in much of southeastern Brazil's vegetation. Three fragments of a Seasonally Dry Tropical Forest (SDTF) located in the southern range of the Espinhaço Mountains were selected for study in the first survey of galling organisms in such tropical vegetation. Investigators found 92 distinct gall morphotypes on several organs of 51 host plant species of 19 families. Cecidomyiidae (Diptera) was the most prolific gall-inducing species, responsible for the largest proportion of galls (77%) observed. Leaves were the most frequently galled plant organ (63%), while the most common gall morphotype was of a spherical shape (30%). The two plant species, Baccharis dracunculifolia (Asteraceae) and Celtis brasiliensis (Cannabaceae), presented the highest number of gall morphtypes, displaying an average of 5 gall morphotypes each. This is the first study of gall-inducing arthropods and their host plant species ever undertaken in a Brazilian SDTF ecosystem. Given the intense human pressure on SDTFs, the high richness of galling arthropods, and implied floral host diversity found in this study indicates the need for an increased effort to catalogue the corresponding flora and fauna, observe their intricate associations and further understand the implications of such rich diversity in these stressed and vulnerable ecosystems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".