Normal Table of <i>Xenopus</i> development: a new graphical resource
Bibliographic record
Abstract
Normal tables of development are essential for studies of embryogenesis, serving as an important resource for model organisms, including the frog Xenopus laevis. Xenopus has long been used to study developmental and cell biology, and is an increasingly important model for human birth defects and disease, genomics, proteomics and toxicology. Scientists utilize Nieuwkoop and Faber's classic 'Normal Table of Xenopus laevis (Daudin)' and accompanying illustrations to enable experimental reproducibility and reuse the illustrations in new publications and teaching. However, it is no longer possible to obtain permission for these copyrighted illustrations. We present 133 new, high-quality illustrations of X. laevis development from fertilization to metamorphosis, with additional views that were not available in the original collection. All the images are available on Xenbase, the Xenopus knowledgebase (http://www.xenbase.org/entry/zahn.do), for download and reuse under an attributable, non-commercial creative commons license. Additionally, we have compiled a 'Landmarks Table' of key morphological features and marker gene expression that can be used to distinguish stages quickly and reliably (https://www.xenbase.org/entry/landmarks-table.do). This new open-access resource will facilitate Xenopus research and teaching in the decades to come.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.688 | 0.349 |
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".