Hydrographic and pore water, core incubation, and sediment leachate geochemical data from Ameralik Fjord and Nuup Kangerlua (Godhäbsfjord) in Southwest Greenland, 2019
Bibliographic record
Abstract
This data set includes hydrographic and pore water and core incubation silicic acid concentration and isotope measurements, sediment Si-HCl and Si-Alk contents and isotope measurements, and pore water nutrient, major, and trace element concentrations measured in the fjords Ameralik Fjord and Nuup Kangerlua (Godhäbsfjord) in southwest Greenland. Data was collected during a research expedition, R/V Tulu 2019, in September 2019, as part of ERC funded (678371) project ICY-LAB (Isotope CYcling in the LABrador Sea) and Royal Society funded (RGF\EA\181036) project Biogeochemical Cycling in Greenlandic Fjords. Temperature and salinity data derived from CTD rosette casts were recorded at station AM10 in Ameralik Fjord and station GF-inlet in Nuup Kangerlua. Fjord water sampling was carried out at 2 stations (AM10 and AM12) in Ameralik Fjord and station GF-inlet in Nuup Kangerlua using Towfish and Niskin bottles for near surface and sub surface samples, respectively. For bottle samples, temperature and salinity were measured using an EXO3 Multiparameter Water Quality Sonde. Fjord sediments were collected by a large bore sediment corer (Aquatic Research Instruments) at station AM10a in Ameralik Fjord and station GF-inlet in Nuup Kangerlua. Pore waters were extracted from the sediment cores using Rhizon samplers and core incubation experiments were carried out following the methodology of Hammond et al. (2004, doi:10.4319/lom.2004.2.146). Sediment reactive silica was leached using a sequential extraction method from Michalopoulos and Aller (2004, doi:10.1016/j.gca.2003.07.018) and Pickering et al. (2020, doi:10.1029/2020GL087877).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".