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 article calls attention to the end of a sentence. The end is interesting in that even the strongest end has to be open-ended, to end is for convenience and not to end is always potential. It puts forward three important concepts surrounding the end: the end word, the end space and the regeneration. The end word is the first content word that accomplishes the generation of a sentence; the end space is the paralinguistic space in the form of time following the end word; and the regeneration is the renewal of a sentence that has been sufficiently generated. The regeneration has to happen in the end space. The article demonstrates that great differences lie in the end between languages as exemplified by three major languages, Chinese, English and Japanese. First, one language favors one part of speech while another another part of speech as the end words; second, different languages send different agents into the end space; and third, different agents possess different power of regeneration. These differences have a lot to say about different ways of thinking in languages, and an awareness of them will help deal with cross-lingual barriers.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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