Bibliographic record
Abstract
1 More than 200 known species of Microturbellaria occur in running waters world-wide but discovery of many more is likely. Their population density varies greatly as a function of substratum, productivity, phenology and hydrology. The density may exceed 7 000 individuals m-2. The number of species in a single small sample may reach 20. 2 Many species appear to have microhabitat or stream section specialisation but community patterns are obscured to a certain extent by common and eurytopic species. The specialisation is particularly evident in the smaller, lower-order streams. 3 Some of this habitat specialisation is attributable to the ecological origin of species that may include terrestrial, underground, marine and lentic species pools. 4 Feeding habits of Microturbellaria range from omnivory to specialised predation. 5 Quantitative field studies require extraction and examination of live specimens from samples. Such samples pose transportation and storage problems and must be processed within hours of collection. 6 Taxonomy is well resolved for the Northern Hemisphere but is likely to be a major challenge in other parts of the world. In any region, however, new species may demand caution while using current keys to their identification.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".