OSNAP mooring CSI1 on the Newfoundland and Labrador shelf
Bibliographic record
Abstract
Mooring data collected on the Newfoundland and Labrador (NL) shelf in support of the Overturning in the Subpolar North Atlantic Program (OSNAP). The Canadian mooring 1 along Seal Island section (OSNAP mooring CSI1) is equipped with Conductivity-Temperature-Depth (CTD), Acoustic Doppler Current Profiler (ADCP) and other temperature-only sensors. It has been deployed since July 2020 at geographical location 53.4490 degrees north and 55.2995 degrees west. Please refer to the OSNAP data management plan for more details regarding the OSNAP data policy and management plan. Before the use and publication of any OSNAP data, users are strongly encouraged to read the full OSNAP data policy. We draw your attention to the following excerpts from that policy: Any person making use of OSNAP observational data and/or numerical results must communicate with the responsible investigators at the start of the analysis and anticipate that the data collectors will be co-authors of published results. In cases where investigators choose not to be co-authors on publications that rely on their data, the parties responsible for collecting the data and the sponsoring funding agencies should be acknowledged, including reference to any relevant publications by the originating authors describing the data sets and a reference to the data set itself using its DOI. OSNAP data are intended for scholarly use by the academic and scientific community, with the express understanding that any such use will properly acknowledge the originating investigator. HOW TO ACKNOWLEDGE DATA FROM THE OSNAP PROJECT: OSNAP data were collected and made freely available by the OSNAP (Overturning in the Subpolar North Atlantic Program) project and all the national programs that contribute to it (www.o-snap.org).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".