2016-2017 Field deployment data from Arctic Lakes in Northwest Territories, Canada: L80
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
Data from Lake 80. Time series data from sensors and water samplers deployed as OsmoSamplers at the bottom of seasonally ice-covered permafrost lakes in the Mackenzie River delta, Northwest Territories, Canada, from 2016 -2017. Sensor data includes water temperature, pressure, dissolved oxygen, light, and conductivity. Water samples were analyzed for dissolved major, minor and trace ions and methane concentrations. Study lakes include four lakes near Inuvik in the mid-delta (Lakes 56, 129, 280, and 520), two lakes in the outer delta near the outflow of the Middle Channel (informally named Swiss Cheese and Manta Lakes), and two lakes on North Richards Island (informally named North Head sites 1 and 2).
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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