Bibliographic record
Abstract
We typically think of predators as animals that kill and eat other animals, such as lions eating zebra, or spiders eating flies. These are true predators that consume prey animals to obtain food for their own survival and reproduction. However, there are other types of predators that have some but not all of the features of true predators. These include parasitoids , which are hymenopterans or dipterans that are free-living in the adult stage, but whose larvae live in or on other arthropods (usually insects), doing little harm at first but eventually consuming and killing the host just prior to pupation. There are also plant and animal parasites that live in an obligatory relationship with another species, and harm their hosts, but usually do not kill it. Then there are animals that eat plants, the herbivores . Seed-eating herbivores act like true predators, because they consume all of their ‘prey’. Others act rather like parasites, because they live in close association with the plant and derive their nourishment from it (e.g. aphids). However, the majority of herbivores only consume a part of the plant, and their detrimental effects can be very variable. Partial or complete defoliation of a plant may have a large effect on the plant's fitness, by reducing its growth rate and seed production, and possibly leaving the plant more vulnerable to attack by plant pathogens.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.021 |
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".