Bibliographic record
Abstract
Scales bridging problem has been studied in mathematics and the natural sciences for decades. In this study we concentrate on a model of growth of animals. The model of growth of pigs was built in two different techniques continuum, and non-local. The both techniques model the same process and use the same variables. However, the outcomes that one can acquire from them are different. In this study, in this model, the problem how to bridge scales between genotype, and phenotypes of ontogenetic growth remain intact; it has not been considered. We narrowed the gap instead and discussed scales bridging problem between biochemistry of digestion, and the growth of animals. This range of scales the model potentially can bridge. In this study we discuss what does it mean bridge a scale. How to identify the scale to bridge. What means one has, to perform it. In this research non-local modelling technique was used. It was shown that this technique has sufficient power to make known emergent events in animals’ growth. The use of the non-local modelling technique to bridge the scale was discussed.    
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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".