Bibliographic record
Abstract
BACKGROUND: A recent study by Tadepally et al. describes the clustering of zinc finger (ZF) genes in the human genome and traces their evolutionary history among several placental mammals with complete or draft genome sequences. One of the main conclusions from the paper is that there is a dramatic rate of gene duplication and gene loss, including the surprising result that 118 human ZF genes are absent in chimpanzee. The authors also present evidence concerning the ancestral order in which the ZF-associated KRAB and SCAN domains were recruited to ZF proteins. RESULTS: Based on our analysis of two of the largest human ZF gene clusters, we find that nearly all of the human genes have plausible orthologs in chimpanzee. The one exception may be a result of the incomplete sequence coverage in the draft chimpanzee genome. The discrepancy in gene content analysis may result from the authors' dependence on the preliminary NCBI gene prediction set for chimpanzee, which appears to either fail to predict or to mispredict many chimpanzee ZF genes. Similar problems may affect the authors' interpretation of the more divergent dog, mouse, and rat ZF gene complements. In addition, we present evidence that the KRAB domain was recruited to ZF genes before the SCAN domain, rather than the reverse as the authors suggest. This discrepancy appears to result from the fact that the SCAN domain did indeed arise before the KRAB domain but is present only in non-ZF genes until a much later date. CONCLUSION: When comparing gene content among species, especially when using draft genome assemblies, dependence on preliminary gene prediction sets can be seriously misleading. In such studies, genic sequences must be identified in a manner that is as independent as possible of prediction sets. In addition, we present evidence that provides a more parsimonious explanation for the large proportion of mammalian KRAB-ZF genes without a SCAN domain.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".