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
The ocean exerts a pervasive influence on Earths environment. It is therefore important that we learn how this system operates (NRC, 1998b; 1999). For example, the ocean is an important regulator of climate change (e.g., IPCC, 1995). Understanding the link between natural and anthropogenic climate change and ocean circulation is essential for predicting the magnitude and impact of future changes in Earths climate. Understanding the ocean, and the complex physical, biological, chemical, and geological systems operating within it, should be an important goal for the opening decades of the 21st century. Another fundamental reason for increasing our understanding of ocean systems is that the global economy is highly dependent on the ocean (e.g., for tourism, fisheries, hydrocarbons, and mineral resources) (Summerhayes, 1996). The establishment of a global network of seafloor observatories will help to provide the means to accomplish this goal. These observatories will have power and communication capabilities and will provide support for spatially distributed sensing systems and mobile platforms. Sensors and instruments will potentially collect data from above the air-sea interface to below the seafloor. Seafloor observatories will also be a powerful complement to satellite measurement systems by providing the ability to collect vertically distributed measurements within the water column for use with the spatial measurements acquired by satellites while also providing the capability to calibrate remotely sensed satellite measurements (NRC, 2000). Ocean observatory science has already had major successes. For example the TAO array has enabled the detection, understanding and prediction of El Niño events (e.g., Fujimoto et al., 2003). This paper is a world-wide review of the new emerging Seafloor Observatory Science, and describes both the scientific motivations for seafloor observatories and the technical solutions applied to their architecture. A description of world-wide past and ongoing experiments, as well as concepts presently under study, is also given, with particular attention to European projects and to the Italian contribution. Finally, there is a discussion on Seafloor Observatory Science perspectives.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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