Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In systematic biology homology hypotheses are typically based on points of similarity and tested using congruence, of which the two stages have come to be distinguished as “primary” versus “secondary” homology. Primary homology is often regarded as prior to logical test, being a kind of background assumption or prior knowledge. Similarity can, however, be tested by more detailed studies that corroborate or weaken previous homology hypotheses before the test of congruence is applied. Indeed testing similarity is the only way to test the homology of characters, as congruence only tests their states. Traditional homology criteria include topology, special similarity, function, ontogeny and step‐counting (for example, transformation in one step versus two via loss and gain). Here we present a method to compare quantitatively the ability of such criteria, and competing homology schema, to explain morphological observations. We apply the method to a classic and difficult problem in the homology of male spider genital sclerites. For this test case topology performed better than special similarity or function. Primary homologies founded on topology resulted in hypotheses that were globally more parsimonious than those based on other criteria, and therefore yielded a more coherent and congruent nomenclature of palpal sclerites in theridiid spiders than prior attempts. Finally, we question whether primary homology should be insulated as “prior knowledge” from the usual issues and demands that quantitative phylogenetic analyses pose, such as weighting and global versus local optima. © The Willi Hennig Society 2007.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it