Manipulation of host food availability and use of multiple exposures to assess the crowding effect on<i>Hymenolepis diminuta</i>in<i>Tribolium confusum</i>
Bibliographic record
Abstract
We studied the 'crowding effect' in Tribolium confusum infected with Hymenolepis diminuta. Manipulations included age and number of parasites, and diet, sex, age and number of exposures of hosts. Volume per parasite was unaffected until an intensity of at least 5-10 parasites per host, then declined approximately inversely as intensities increased. Parasite size was affected by host sex but not age or reproductive status. Host diet affected parasite size and the impact of crowding. Daily gain in parasite volume peaked partway through the developmental period and preceded the first evidence of a crowding effect. Parasites that established during a second exposure had a transient developmental delay but eventually grew as large or larger than parasites from a single exposure with the same total intensity. Parasites responded to crowding by differential allocation of resources. Cercomer volume decreased even with slight crowding, the capsule surrounding the scolex was not reduced until crowding became more severe, and scolex width was reduced only in the most extreme conditions. The data support the hypothesis that the crowding effect in this system is driven primarily by nutrient, rather than space limitations.
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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 | 0.000 | 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 | 0.001 |
| 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".