Global Ocean Data Analysis Project version 2.2023 (GLODAPv2.2023) (NCEI Accession 0283442)
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
This dataset consists of the GLODAPv2.2023 data product composed of data from 1108 scientific cruises covering the global ocean between 1972 and 2021. It includes full depth discrete bottle measurements of salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon (TCO2), total alkalinity (TAlk), CO2 fugacity (fCO2), pH, chlorofluorocarbons (CFC-11, CFC-12, CFC-113, and CCl4), SF6, and various isotopes and organic compounds. It was created by appending data from 23 cruises to GLODAPv2.2022 (Lauvset et al., 2022, NCEI Accession 0257247). The data for salinity, oxygen, nitrate, silicate, phosphate, TCO2, TAlk, pH, CFC-11, CFC-12, CFC-113, CCl4, and SF6 were subjected to primary and secondary quality control. Severe biases in these data have been corrected for, and outliers removed. However, differences in data related to any known or likely time trends or variations have not been corrected for. These data are believed to be accurate to 0.005 in salinity, 1% in oxygen, 2% in nitrate, 2% in silicate, 2% in phosphate, 4 µmol kg-1 in TCO2, 4 µmol kg-1 in TAlk, and for the halogenated transient tracers and SF6: 5%.
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 | 0.043 | 0.151 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.040 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.016 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.098 |
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