Bibliographic record
Abstract
Once three had been snow. There had been vastly blinding seas as hard as rock and bone-penetrating cold. So much had depended upon the game animals that when they fled eastward, over the ice-locked Bering straits, The People followed them into a new land. Here, too, winters were white with swirling blizzards; here too the ice boomed in the rivers like thunder when it broke late in the spring. But not all of The People stayed with winter. Some followed game ever southward toward the spring. During the first few generations of the journey, veterans of it dwelt, first, on experience, and, then, on traditions of what men would later call Siberia, Alaska, and Canada. But gradually the racial memory died. The southern sun burned, soft rains fell, and coastal palm fronds stirred in the wind. The People, those of them who had come into Alabama and Georgia, made legends then, and the legends were of what they now knew: alligators, snakes, the deer of the dark forests, the fish in the sea, the peninsula south of the tribe, perhaps even forays there and into Mexico as well.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.644 | 0.331 |
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".