Uncertainty in a situation analysis perspective
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
This paperproposes a discussion on the role of iincerfainty in situation analysis. An overview of the princi- pal typologies of uncertainty foundin the recent literuture is presented. This wide array of uncet-tainty conceptions is a consequence of the intrinsic richness and ambiguity of nat- ural language, but also a consequence of the complexplivs- ical nature of information. Definitions of a liniited number of concepts are proposed in order to better understand the diflerent facets of uncertainty. The benefits sought are: (I) the avoidance of untimely uses of dejniriorls and models of uncertainty. (2) clarifications allowing links with the al- ready well developed logics of knowledge and belief; and (3) guidelines for the selection of the appropriate mathe- matical model to process uncertainty-based information.
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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 | 0.002 |
| 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