Bibliographic record
Abstract
Menno Reindert Kruk was born in 1944 in the Netherlands. He did his PhD on the ‘Origins of Hypothalamic Aggression’ and became President of the International Society for the Study of Aggression. He coordinated Hungarian-Dutch cooperation on ‘Stress and Aggression Interactions’ and an interdisciplinary multicenter research program on the ‘Neuroanatomy and Temporal Structure of Hypothalamic Responses’. His main research focus was the interaction between brain function, hormones, and behavior, with the aim of understanding brain mechanisms during violent behavior. He specifically explored how aggression could be studied using methods from the natural sciences and animal models, first to clarify which hypothalamic neurons mediate attack during electrical stimulation and then to register their activity during social interactions in order to understand ‘pathological’ processes in aggression. The research methods he used included ethological, pharmacological, endocrine, physiological, and mathematical approaches. He developed animal models of functional and pathological aggression and the mathematical tools to describe and analyze the effects of drugs and hormones on behavioral structure and on social interactions between animals. He studied the crucial role of corticosteroid feedback to the brain for the control of aggressive behavior and studied the interactions between the processing of conflict-related stimuli and stress hormones in humans.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.014 |
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".