The Economic Efficiency of Homomorphic Model
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Bibliographic record
Abstract
<p class="zhengwen">This paper assesses the closeness of the degree of similarity between the behaviour of a model and the actual product according to technical and economic criteria. The methodology is illustrated on the example of a power boat and a sailing boat model. The first part deals with technical aspects, using the cybernetic theory of similarities – classification of the relationship between the model and the actual product (isomorphic or homomorphic). Since in this case the similarity was assessed in the area of aerodynamics, the Bernoulli Equation was used to derive the conditions of isomorphism for flow in the actual object. This defines the boat model from the technical point of view.</p> Because, in the attempt to develop the best possible value-for-money products, dictated by the market competitiveness, fixed costs play a major role, so it is necessary to complement technical information with economic laws. Based on these, it is then possible to select either the homomorphic model (the one which does not meet all requirements on similarity) or the isomorphic model (the one which more closely conforms to the actual product). Here the economic aspects of the model’s feasibility is assessed in three different dimensions which mutually interact with each other: The first dimension deals with the question of whether the product is for the customer segment for which it is intended, the correct value proposition, (using either the Boston Matrix or the GE Matrix as a tool). The second dimension answers the question of whether a typical customer is not too costly to service, and the last dimension assesses the closeness of the model’s similarity according to the criteria of flexibility of the demand function. Thus the primary objective of this paper is to mathematically derive the criteria of similarity between the model and the product. This criterion represents the criterion of the model’s technical limitations. In order to optimise the selection of most suitable model under the circumstances (for the given product), it is also necessary to take into account the mutually interacting economic criteria. To provide an understanding how these economic criteria interact with each other is another objective of this paper.
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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 | 0.001 | 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 it