Bibliographic record
Abstract
The launching of a new journal combining two previously disparate disciplines heralds a new era in the annals of human anatomy and developmental biology.The recent advances in embryology and genetics are increasingly integrating the interaction of genetic directives and embryological dispensation in the development of "De humani corporis fabrica" [1].The founders of genetics, Mendel, Bateson, Dobzhansky and Muller could not have imagined the impact that their disciplines have had in advancing the developmental phenomena of embryology.Nor would the pioneers of embryology, their names embedded in Meckel's cartilage, the Eustachian tube, the Gasserian ganglion and the Malpighian corpuscles of the kidney have dreamt of their exploratory sciences being driven by genes that were only revealed by the sequencing of the human genome in 2001 [2].Among the first textbooks to meld the two sciences were Scott Gilbert's "Developmental Biology" [3], Wolpert's "Principles of Development" [4] and Sperber's "Craniofacial Embryogenetics and Development" [5].These books integrate embryological phenomena driven by genetic signaling networks.The detailed identification of discrete components of the constantly changing developing embryo by sophisticated selective
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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 | 0.021 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.003 | 0.050 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".