Bibliographic record
Abstract
Aim Recent comparisons of different approaches to historical biogeography have suffered in part because Brooks Parsimony Analysis (BPA) has been characterized as a one‐step process following protocols proposed in 1981. Subsequent modifications have resulted in a two‐step methodology. This contribution presents the mechanics and applications of those modifications. Methods The first step, or Primary BPA, which is similar to the original BPA but with modifications proposed by Wiley (1986 , 1988a , b ), is used to assess whether or not there is support for a single general area cladogram. The second step, Secondary BPA, proposed by Brooks (1990) , depicts exceptions to the general area cladogram explicitly by duplicating areas having a reticulate history. Results The analytical basis of area duplication in secondary BPA is explained more fully than in previous accounts, and the manner in which secondary BPA explicitly depicts falsification of the null hypothesis of simple vicariance is presented for four general cases. Main conclusions BPA, as fully implemented, is capable of accounting for the complexity of speciation, dispersal and extinction events in a historical biogeographic context without removing or modifying input data from basic phylogenies, so long as at least three clades are analysed simultaneously to provide a distinction between general and special distribution elements.
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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 | 0.022 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.039 | 0.041 |
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".