ARGO_BGC dataset for the Labrador Sea region
Bibliographic record
Abstract
ARGO_allVars_1mRes_450.tgz: archive contains Matlab binary files consisting of all ARGO_BGC float data in the Labrador Sea. Profile data were interpolated to 1m vertical resolution and are given up to a water depth of 450 meter. Dataset includes information on date, latitude, longitude, salinity, temperature, Chlorophyll-a, particle backscatter (bbp), and (not available on all floats) Oxygen, Nitrogen and Photosynthetically available radiation (PAR). ARGO_physic_5mRes_5000.tgz: archive contains Matlab binary files consisting of all ARGO physical data in the Labrador Sea. Profile data were interpolated to 5m vertical resolution and are given up to a water depth of 5000 meter. Dataset includes information on date, latitude, longitude, salinity, temperature. CMEMS_along_ARGO_physicsFine.tgz: archive contains Matlab binary files consisting of CMEMS high resolution physical model data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, salinity, temperature and CMEMS model depths. CMEMS_along_ARGO_chlCoarse.tgz: archive contains Matlab binary files consisting of CMEMS coarse BGC-model data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, Chlorophyll-a and CMEMS model depths. CMEMS_along_ARGO_chlOCL3.tgz: archive contains Matlab binary files consisting of CMEMS Level 3 Chlorophyll-a remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a. CMEMS_along_ARGO_chlOCL4.tgz: archive contains Matlab binary files consisting of CMEMS Level 4 Chlorophyll-a remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a. MODIS_along_ARGO.tgz: archive contains Matlab binary files consisting of MODIS-Aqua Level 3 remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a, (surface) particle backscatter and Photosynthetically available radiation (PAR).
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.061 |
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".