Ending a decade of deception: a valiant failure, a not‐so‐valiant failure, and a success story
Bibliographic record
Abstract
Prior studies involving two methods, Brooks Parsimony Analysis (BPA) and TreeMap, have found BPA to be the more reliable method. Recent criticisms leveled at these studies argue that the tests were unfairly created and biased in favor of BPA. The authors of a recent critique offered new exemplars to demonstrate flaws in BPA, plus a simple fix to correct the flaws found in TreeMap. A re-evaluation of their exemplars clearly shows that the authors' calculations are incorrect, their understanding of the methods is lacking, and that their simple fix does not work. Additional analyses using TreeMap 2.02 are run to show that TreeMap 2.02, like TreeMap 1.0, cannot adequately deal with widespread parasites, contrary to the claims of its supporters. Furthermore, the exemplars corroborate previous findings that BPA, when calculated correctly, is more reliable than TreeMap1.0 and TreeMap 2.02 and therefore the method of choice in coevolutionary and biogeographic studies.
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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 | 0.062 | 0.209 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.046 |
| Scholarly communication | 0.013 | 0.031 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.011 | 0.026 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".