Parasite specialization from a phylogenetic perspective: a new index of host specificity
Bibliographic record
Abstract
The host specificity of a parasite is not merely a function of how many host species it can exploit, but also of how closely related these host species are to each other. Here, a new index of host specificity is proposed, one that takes into account the average taxonomic or phylogenetic distance between pairs of host species used by a parasite. The index is derived from measures of taxonomic distinctness used in biodiversity studies. It is easy to compute and interpret, ranging from a minimum value of 1 when all host species are members of the same genus, to a maximum of 5, when all host species belong to different classes. The variance of this measure can also be computed, and provides additional information on the taxonomic or phylogenetic structure of the host assemblage. Using data on helminth parasites of Canadian freshwater fishes, we show that the new index, unlike the mere number of known host species, is independent of study effort i.e. the number of published records of a parasite. Although the index and the number of known hosts are not entirely independent statistically, each captures a different aspect of host specificity. For instance, although acanthocephalans infect significantly more host species than trematodes, cestodes or nematodes, there is no difference in the average index value among these 4 helminth taxa, suggesting that the average taxonomic distances between the host species of a parasite do not vary among these higher taxa. We recommend the use of our new index in future comparative studies of host specificity, in particular when the focus is on the evolutionary history of parasites and of their past colonizations of host lineages.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".