Bibliographic record
Abstract
SCIENTISTS would knowall or in partJust how the end of the worldwill start–Whether by a moment ofblinding flashSo quick in it’s onsetI am already ashOr if a discoveryfinally decodedIs summated in a cataclysmforboded–I may have time toraise my eyesAt the tidal wavesof falling skiesOr perhaps I wouldlong contemplateThe fireworks of my unchangeableFate-Now little child,you arrive to meFor this week’schemotherapy–Gone are your curlylocks of hairlike the fur worn on yourTeddy bearWith experienceyou askIf you can have the IVinstead of the maskYou hate to go to sleepEach timeWon’t watch the drugs flowthrough the lineAnd there you go–a dreamless sleepA time for mom and dadto weepThe job is doneIt’s time to wakeThe spark returnsa moment it takesBored already–it’s time to goThis: your worldis all you knowI move on to the nextJust a little unsteadyand wonder if the endHasn’t come already.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.486 | 0.234 |
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 source (direct Gemma or distilled Codex), 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".