Bibliographic record
Abstract
Since the pioneering work of Ethel Browne (1909) who demonstrated for the first time the concept of organizer activity, i.e. the potency of an apical Hydra tissue to induce a secondary axis when transplanted onto a host, Hydra flourished as a fruitful model system for developmental studies. Over the next 60 years this efficient transplantation approach identified graded biological activities along the body column of Hydra named Head Acti-vation and Head Inhibition. These properties inspired theoretical modelers including Lewis Wolpert, Alfred Gierer and Hans Meinhardt to propose models for morphogenesis, respectively the positional information (1969) and reaction-diffusion (1972) models. In 1973, Tsutomu Sugiyama and Toshitaka Fujisawa initiated in Mishima a unique project to analyze the properties of Hydra strains with distinct morphological and developmental characters. To this end, they collected in several areas of Japan multiple Hydra strains that they subsequently characterized and crossed. They also established a lateral transplantation strategy that was much more powerful than the previous ones, as it combined quantitative measurements with cellular analyses thanks to the chimera procedures developed by Campbell and colleagues. In-deed this approach provided a paradigm to quantify in any morphological phenotype the Head Activation and Head Inhibition levels along the body column. In this article, I review the various strains identified by Sugiyama and colleagues, the principles and the main results deduced from the quantitative lateral transplantation strategy. In addition, I briefly discuss the relevance of this approach in the era of molecular biology.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".