Grouping Product Variants based on Alternate Machines for Each Operation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A new method for calculating the commonality between product variants in terms of machine usage is proposed. Grouping products has been studied by various authors under different titles such as product family formation, cell formation, part-machine groups formation. However, having more than one alternative machine that can be selected for performing an operation has not been considered in the area of grouping product variants. In this paper, it is assumed that each product variant requires some operations and for each operation there exist some alternative machines. The focus is on grouping the products and consequently, building a dendogram based on commonality. A new method for grouping the products is proposed and a dendogram is depicted by using Average Linkage Clustering (ALC). The resulting dendogram is very helpful as it shows the levels of similarity between product variants and can be further used by product designers, process planners and production planners.
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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 | 0.001 |
| 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 | 0.001 |
| 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