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
Abstract On the basis of cross-linguistic data from both genetically and geographically related and unrelated languages, in this article we argue that the linguistic phenomena usually referred to as the avertive, the frustrative and the apprehensional belong not to three but to five – semantically related, and yet distinct grammatical categories, all of which involve different degrees of non-realization of the verb situation in the area of Tense-Aspect-Mood: apprehensional, avertive, frustrated initiation, frustrated completion, inconsequential. Our major goal here is to account for these grammatical categories in terms of an adequate model of linguistic categorization. For this purpose, we apply the notion of Intersective Gradience (introduced for the first time in the morphosyntactic domain in Aarts ( 2004 , 2007 ) to the morphosemantic domain. Thus the present approach reconciles two major approaches to linguistic categorization: (i) the classical, Aristotelian approach and (ii) a more recent, gradience/fuzziness approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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