The COCO/sup DEF/ approach to COCOLOG logic control
Bibliographic record
Abstract
In this paper, we present the application of Macro COCOLOG definition expressions to COCOLOG control theories themselves. In particular, the reachability relation on systems which can be modeled in COCOLOG is shown to have a definition in a subset of the basic axiom set of COCOLOG. The definition of the reachability predicate is then explored in the light of possible extensions to the arithmetic system in COCOLOG. Given the fact that reachability is a fundamental system-theoretic concept, the definition expression describing this predicate is given the special status of a definitional axiom. The application of definability theory to COCOLOG control theories then gives rise to COCO/sup DEF/, in which the original COCOLOG framework is shown to have an equivalent definitional framework. Furthermore, Macro actions themselves are shown to have a definitional expression equivalent to them. A couple of examples used elsewhere in the Macro COCOLOG framework are then reformulated to show the application of this approach.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".