Morphology and Biometry of Nebela tenella Penard, 1893 (Amoebozoa:Arcellinida)
Bibliographic record
Abstract
Shell ultra-structure and morphometrical variability of Nebela tenella were investigated using scanning electron microscopy (SEM). N. tenella was isolated from two widely separated populations, one from Switzerland and another from Canada. The shell’s structural elements were similar to those of the other nebelids, but N. tenella has a characteristic peculiarity – always present depressions on the shell surface, which makes an uneven outline of the shell. Moreover, light microscopy and SEM study showed that the collar of the N. tenella represents a turned-over continuation of the neck, which is covered by the same idiosomes as on the shell body. The biometrical analysis showed that the majority of the basic characters of N. tenella vary moderately and give continuous series of transition forms. According to the shell depth and the ratio depth/width both populations were significantly different of each other. Variation coefficients showed that the variability of the characters differs in both populations and the Swiss population is more stable than the Canadian one. All new obtained data for N. tenella raise the question whether the shell’s size, cross section and ultramorphology are reliable enough as characters for the differentiation of N. tenella and N. griseola, and whether they are two distinct species or should just be considered as ecophenotypic variation within one species?
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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 | 0.000 | 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) | 0.001 | 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".