The Ontological Stance for a Manufacturing Scenario
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
The semantic integration of software systems can be supported through a shared understanding of the terminology in their respective ontologies. In practice, however, the author is faced with the additional challenge that few applications have an explicitly axiomatized ontology. To address this challenge, we adopt the Ontological Stance, in which we can model a software application as if it were an inference system with an axiomatized ontology, and use this ontology to predict the set of sentences that the inference system determines to be entailed or satisfiable. This chapter gives an overview of a deployment of the Process Specification Language (PSL) Ontology as the interchange ontology for the semantic integration of three manufacturing software applications currently being used in industry -- a process modeller, a process planner, and a scheduler.
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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 | 0.000 | 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 | 0.001 | 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