An experimental test of the independent action hypothesis in virus–insect pathosystems
Bibliographic record
Abstract
The 'independent action hypothesis' (IAH) states that each pathogen individual has a non-zero probability of causing host death and that pathogen individuals act independently. IAH has not been rigorously tested. In this paper, we (i) develop a probabilistic framework for testing IAH and (ii) demonstrate that, in two out of the six virus-insect pathosystems tested, IAH is supported by the data. We first show that IAH inextricably links host survivorship to the number of infecting pathogen individuals, and develop a model to predict the frequency of single- and dual-genotype infections when a host is challenged with a mixture of two genotypes. Model predictions were tested using genetically marked, near-identical baculovirus genotypes, and insect larvae from three host species differing in susceptibility. Observations in early-instar larvae of two susceptible host species support IAH, but observations in late-instar larvae of susceptible host species and larvae of a less susceptible host species were not in agreement with IAH. Hence the model is experimentally supported only in pathosystems in which the host is highly susceptible. We provide, to our knowledge, the first qualitative experimental evidence that, in such pathosystems, the action of a single virion is sufficient to cause disease.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".