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 Iceberg Beacon Track Database is a collection of 224 iceberg drift tracks with a total of 719,045 positions from the Arctic and (North) Atlantic oceans. Each track is accompanied by metadata that describes the iceberg shape, dimensions (m), beacon model, and other ancillary information that can be used in research related to iceberg drift climatology, developing and validating drift models, and validating remote sensing iceberg detection algorithms. The beacon tracks were collected by 12 academic, industry, and government research groups from 1997 to 2025. They all include timestamps (UTC) and position data (latitude and longitude: dd.dddd°), and may include temperature (K), barometric pressure (Pa), heading, pitch, and roll (degrees). All beacon tracks have been processed and consolidated into the same framework, and are available in geospatial formats for mapping and analysis. Although the current data extent is largely within Canadian waters, we consider all drift tracks of Northern Hemisphere icebergs and related features (ice islands, bergy bits, and other fragments) to be within the scope of this collection. We encourage those who have beacon tracks to submit them for inclusion into subsequent versions of the Iceberg Beacon Track Database.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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