Report of the SNOMS Project 2006 to 2012, SNOMS SWIRE NOCS Ocean Monitoring System. Part 1: Narrative description
Bibliographic record
Abstract
The ocean plays a major role in controlling the concentration of carbon dioxide (CO2) in the atmosphere. Increasing concentrations of CO2 in the atmosphere are a threat to the stability of the earth’s climate. A better understanding of the controlling role of the ocean will improve predictions of likely future changes in climate and the impact of the uptake of CO2 itself on marine eco-systems caused by the associated acidification of the ocean waters. The SNOMS Project (SWIRE NOCS Ocean Monitoring System) is a ground breaking joint research project supported by the Swire Group Trust, the Swire Educational Trust, the China Navigation Company (CNCo) and the Natural Environment Research Council. It collects high quality data on concentrations of CO2 in the surface layer of the ocean. It contributes to the international effort to better quantify (and understand the driving processes controlling) the exchanges of CO2 between the ocean and the atmosphere. \n \nIn 2006 and 2007 a system that could be used on a commercial ship to provide data over periods of several months with only limited maintenance by the ships crew was designed and assembled by NOCS. The system was fitted to the CNCo ship the MV Pacific Celebes in May 2007. The onboard system was supported by web pages that monitored the progress of the ship and the functioning of the data collection system. To support the flow of data from the ship to the archiving of the data at the Carbon Dioxide Information Analysis Center (CDIAC in the USA) data processing procedures were developed for the quality control and systematic handling of the data. Data from samples of seawater collected by the ships crew and analysed in NOC (730 samples) have been used to confirm the consistency of the data from the automated measurement system on the ship. \n \nTo examine the data collected between 2007 and 2012 the movements of the ship are divided into 16 voyages. Initially The Celebes traded on a route circum-navigating the globe via the Panama and Suez Canals. In 2009 the route shifted to one between Australia and New Zealand to USA and Canada. Analysis of the data is an on going process. It has demonstrated that the system produces reliable data. Data are capable of improving existing estimates of seasonal variability. The work has improved knowledge of gas exchange processes. Data from the crew-collected-samples are helping improve our ability to estimate alkalinity in different areas. This helps with the study of ocean acidification. Data from the 9 round trips in the Pacific are currently being examined along with data made available by the NOAA-PMEL laboratory forming time series from 2004 to 2012. The data from the Pacific route are of considerable interest. One reason is that the data monitors variations in the fluxes of CO2 associated with the current that flows westwards along the equator. This is one of the major natural sources of CO2 from the ocean into the atmosphere.
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How this classification was reachedexpand
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 | 0.046 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.010 | 0.015 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.009 |
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; both teacher heads agree on what is shown here.
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".