Global temperature and salinity profile programme (GTSPP)- Data user's manual, first edition
Bibliographic record
Abstract
The Global Temperature and Salinity Profile Programme (GTSPP) is a joint Intergovernmental Oceanographic Commission (IOC) and World Meteorological Organization (WMO) programme to develop and maintain a global ocean Temperature-Salinity resource with data that are both up-to-date and of the highest quality[2]. The four primary objectives of GTSPP are: \na) Provide a timely and complete data and information base of ocean temperature and salinity profile data, \nb) Implement data flow monitoring system for improving the capture and timeliness of real-time and delayed-mode data, \nc) Improve and implement agreed and uniform quality control and duplicates management systems, and \nd) Facilitate the development and provision of a wide variety of useful data analyses, data and information products, and data sets. \nThe international oceanographic community‟s interest in creating a timely global ocean temperature and salinity dataset of known quality in support of the World Climate Research Programme (WCRP) dates back to the 1981 “International Oceanographic Data and Information Exchange” (IODE) meeting in Hamburg, Federal Republic of Germany. The community's interest led to preliminary discussions by the Australian Oceanographic Data Center (AODC), the Marine Environmental Data Service (MEDS), now the Integrated Science Data Management (ISDM), of Canada and the U.S. National Oceanographic Data Center (NODC) during the second Joint IOC–WMO Meeting of Experts on IGOSS1-IODE Data Flow in Ottawa, Canada in January 1988. \nDevelopment of the GTSPP (then called the Global Temperature-Salinity Pilot Project) began in 1989. The short-term goal was to respond to the needs of the Tropical Ocean and Global Atmosphere (TOGA) Experiment and the World Ocean Circulation Experiment (WOCE) for temperature and salinity data. The longer-term goal was to develop and implement an end-to-end data management system for temperature and salinity data and other associated types of profiles, which could serve as a model for future oceanographic data management systems. GTSPP began operation in November 1990. The first version of the GTSPP Project Plan was published in the same year. Since that time, there have been many developments and some changes in direction including a decision by IOC and WMO to end the pilot phase and implement GTSPP as a permanent programme in 1996. \nFigure 1 is a sketch diagramme of the GTSPP management structure. GTSPP reports to the IODE Programme of IOC and the Joint Commission for Oceanography and Marine Meteorology (JCOMM), a body sponsored by WMO and IOC.
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.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.128 | 0.159 |
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".