On the definition of stochastic λ-transducers
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Bibliographic record
Abstract
We propose a formal definition for the general notion of stochastic transducer, called stochastic λ-transducer. Our definition is designed with two objectives in mind: (i) to extend naturally the established notion of stochastic automaton with output—as defined in the classic books of [A. Paz, Introduction to Probabilistic Automata, Academic Press, New York and London, 1971; P. Starke, Abstract Automata, North-Holland, Academic Press, 1972.]—by permitting pairs of input-output words of different lengths; (ii) to be compatible with the more general notion of weighted transducer so that one can apply tools of weighted transducers to address certain computational problems involving stochastic transducers. The new transducers can be used to model stochastic input-output processes that cannot be modelled using classical stochastic automata with output.
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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 | 0.000 |
| 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 | 0.001 | 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