MARES Project: Hydrographic data of the San Jorge Gulf from R/V Coriolis II cruise in 2014
Bibliographic record
Abstract
Abstract. PROMESse (Multidisciplinary program for the study of the ecosystem and marine geology of San Jorge Gulf and the coast of the Province of Chubut) was an international cooperation research program among the Ministry of Science and Technology (MINCyT), the National Scientific and Technical Research Council (CONICET), the Province of Chubut (Argentina) and the University of Quebec at Rimouski (UQAR/ISMER, Canada). Within the framework of this program two projects were carried out, MARES (Marine Ecosystem Health of the San Jorge Gulf: Present status and Resilience capacity) and MARGES (Marine Geology). The main goal of MARES was to conduct a comprehensive study of the dynamics of physical, chemical and biological parameters vitals for the San Jorge Gulf ecosystem. The observational component of this project consisted on a multidisciplinary oceanographic cruise on board of the research vessel Coriolis II in Feb. 2014 integrated by three legs designed to identify and characterize areas of high primary productivity, which will serve as indicators of the ecosystem health. This paper reports the hydrographic data collected during the second leg of the Coriolis II cruise. This leg was aimed to study the frontal dynamics associated to a region of high tidal dissipation rate south of the Gulf, and to study the vertical displacements of the pycnocline at a fixed site in the center of the Gulf mouth. To this end, high-resolution data was collected in the southern tidal front, including quasi-continuous CTD vertical profiles, underway surface temperature and salinity, Scanfish II CTD and shipboard ADCP data. The data sets are available in the National Oceanographic Data Center (NODC) from NOAA. DOI: doi:10.7289/V5MP51J2.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".