Developing Sustainable Technologies for Offshore Seismic Operations
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
Abstract Technology plays an important role in modern economic society. Sustainable technology helps society to preserve ecological balance, but unsustainable technology does the opposite. As such, it is important to use inherently sustainable technologies in every sector of human activities. Oil and gas exploration and development are high technology-based operations. Exploring sustainable technologies in the oil and gas sector can reduce environmental and other impacts. This article examines the sustainability of offshore seismic technologies following a new methodology. In addition to presently available technologies, emerging technologies in this field are also examined. A “natural” technology, dolphin ultrasound communication, which functions similar to other seismic technologies, is selected as a standard. This article identifies that presently available technologies have less impacts than previous technology, but their “sustainability state” is not satisfactory. It also reveals that the mechanism of dolphin communication is a better option compared to presently available technologies. This study shows major differences between inherently sustainable and unsustainable technologies. Finally, the article suggests how to achieve sustainability in technology development in relation to offshore seismic operations.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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