Bibliographic record
Abstract
Aluminum oxide (Al 2 O 3 ), 91, 93, 94 Alzheimer's disease (AD), 93, 94 Animal UN, 127-128, 130 Animals, 125-131, 135-137 Anthropogenic greenhouse gas emissions (GHG), 247-251, 254, 257-258 Antiracist, 68 Archimedes of Syracuse, 433 Arctic, 99-102, 107 Arctic amplification (AA), 302 Arctic ice cover, 271 blocking wind/water interface, 272 climate model results for short and longwave radiation, 268 keeping heat in Arctic Ocean, 266, 268 removal, 269 salinity, reducing, 272 thickness of, 266 Arctic Ocean surface waters, salinity of benefits and challenges of methodology, 280-282 four contributors to salinity reduction in, 272, 273 Halocline phenomenon, 270, 271-272, 277 heat balance of, 269, 270 increasing salinity of, 273-278 Greenland ice sheet melting, reducing, 275-277 mix Arctic Ocean waters, 277-278 river flow to Arctic, reducing, 274-275 mass balance of different flows in and out, 272, 273 methodology, 269-278 overview, 265-268 proposed strategies to increase salinity, 278-280 temperature and salinity difference on seawater density, 272 temperature pattern of, 269, 270
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 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) | 0.415 | 0.149 |
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; both teacher heads agree on what is shown here.
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".