Raman lidar data from Capel Dewi, May 23 - 30 2016
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
These lidar data show the passage of smoke from forest fires in Canada over the lidar site at Capel Dewi near Aberystwyth in Wales. A description of the event is provided in Vaughan et al, Atmos. Chem. Phys., DOI: 10.5194/acp-2017-1181. The files contain the photon-counting signals from the lidar as count-rate*height in km squared (corrected for background and pulse pileup), statistical errors in those signals, and synthetic molecular atmosphere profiles derived from two representative radiosonde stations in the vicinity. The counts have been integrated in time over a night, as follows: May23: 2148 on 23 May to 0309 on 24 May May24: 2126 on 24 May to 2206 on 24 May May26: 2304 on 26 May to 2344 on 26 May May29: 2111 on 29 May to 0331 on 30 May May30: 0036 on 31 May to 0257 on 31 May Cloud prevented night-long observations on these nights - cloud-free profiles were selected and combined by visual examination of the raw data.
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 | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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