Bibliographic record
Abstract
This chapter charts the rise of oceanography as a discipline, from the first European-led age of discovery in the fifteenth century, to the scientific expeditions typified by HMS Challenger’s four-year voyage of 1872. Progress continued into the twentieth century with the increase of laboratories, research vessels and funding programs, such as the International Decade of Ocean Exploration (IDOE). Regional sites in key locations – including Hawaii, Bermuda and Ocean Station Papa in the Gulf of Alaska – have been complemented by satellite imagery of ocean statistics and marine life, starting with the Coastal Zone Color Scanner (CZCS), launched on the Nimbus-7 satellite, in 1978. As our ability to measure and analyze has increased, we are gaining a greater appreciation of the highly complex, interconnected nature of our oceans and the damage we are causing them. Rising sea levels have a profound effect on marine ecosystems, dramatically altering the physiology of organisms (e.g., coral reefs) that are unable to migrate or evolve to adapt to the changes. Such organisms face extinction. Meanwhile, loss of sea ice is altering pathways of ocean circulation, in addition to habitat loss. The sinking waters of subpolar Greenland are significant in the formation of the warm Gulf Stream Current; further disruption to this could alter Europe’s climate irrevocably. Increases in atmospheric CO2 levels are also affecting ocean acidity and salinity. This especially impacts the thousands of species that have evolved with calcified structures, and has potential ramifications for the physiology of all marine inhabitants. The chapter ends on a reflection that, whilst a change in plastic production and consumption may be a relatively easy change to make, there are increasingly significant threats to marine ecosystems. Not least of these is deep sea mineral exploration, to which microorganisms, which have survived for billions of years, may adapt, but we most certainly will not if the current changes continue unabated.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.573 | 0.587 |
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".