A priori and a posteriori methods in comparative evolutionary studies of host–parasite associations
Bibliographic record
Abstract
Abstract Brooks parsimony analysis (BPA) and reconciliation methods in studies of host–parasite associations differ fundamentally, despite using the same null hypothesis. Reconciliation methods may eliminate or modify input data to maximize fit of single parasite clades to a null hypothesis of cospeciation, by invoking different a priori assumptions, including a known host phylogeny. By examining the degree of phylogenetic congruence among multiple parasite clades, using hosts as analogs of taxa but not presuming a host phylogeny or any degree of cospeciation a priori, BPA modifies the null hypothesis of cospeciation if necessary to maintain the integrity of the input data. Two exemplars illustrate critical empirical differences between reconciliation methods and BPA: (1) reconciliation methods rather than BPA may select the incorrect general host cladogram for a set of data from different clades of parasites, (2) BPA rather than reconciliation methods provides the most parsimonious interpretation of all available data, and (3) secondary BPA, proposed in 1990, when applied to data sets in which host‐switching produces hosts with reticulate histories, provides the most parsimonious and biologically realistic interpretations of general host cladograms. The extent to which these general host cladograms, based on cospeciation among different parasite clades inhabiting the same hosts, correspond to host phylogeny can be tested, a posteriori, by comparison with a host phylogeny generated from nonparasite data. These observations lead to the conclusion that BPA and reconciliation methods are designed to implement different research programs based on different epistemologies. BPA is an a posteriori method that is designed to assess the host context of parasite speciation events, whereas reconciliation methods are a priori methods that are designed to fit parasite phylogenies to a host phylogeny. Host‐switching events are essential for explaining complex histories of host–parasite associations. BPA assumes coevolutionary complexity (historical contingency), relying on parsimony as an a posteriori explanatory tool to summarize complex results, whereas reconciliation methods, which embody formalized assumptions of maximum cospeciation, are based on a priori conceptual parsimony. Modifications of basic reconciliation methods, embodied in TreeMap 1.0 and TreeMap 2.02, represent the addition of weighting schemes in which the researcher specifies allowed departures from cospeciation a priori, with the result that TreeMap results more closely agree with BPA results than do reconciled tree analysis results.
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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 | 0.054 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".