From observations to paradigms; the importance of theories and models. An interview with Hans Meinhardt
Bibliographic record
Abstract
Hans Meinhardt received his PhD in physics from the University of Cologne at 1966. For a postdoctoral fellowship, he went to the European High Energy Laboratory CERN in Geneva where he joined a group working on the leptonic decay of the Xi-minus particle. One of his duties was to perform computer simulations to optimize the complex experimental setup--a skill which turned out to be helpful later on. In 1969 he switched to biology and joined the department of Alfred Gierer at the Max Planck Institute for Developmental Biology (formerly Virus Research) in Tubingen. His interest was focused on mechanisms of biological pattern formation. Using computer simulations as a tool, he developed models for essential steps in development. Most fascinating for him was the possibility to recapitulate and to reconstructusing the computer the genesis of structures where no structures were before and to see how these emerging structures become subsequently further refined. In addition to the interaction with Alfred Gierer and his group working on hydra development, the Max-Planck Institute as a whole provided a very stimulating environment. In the seventies, the work of Klaus Sander on gradients in early insect development was highly influential. Collaboration with Martin Klinger in the eighties revealed that the pigmentation patterns on tropical sea shells are convenient to study highly dynamic patterning processes. The variability and the asthetic beauty of these patterns turned out to result from the chaotic nature of the underlying reactions. Mechanisms deduced from shell patterns became a key to understand other developing systems such as orientation of chemotactic cells or phyllotaxis. Officially Hans Meinhardt retired at the end of 2003. At present he works on refinements and extensions of models which account for the different modes of embryonic axis formation in different phyla from an evolutionary point of view.
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.
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".