Bibliographic record
Abstract
Frontispiece - the global ocean how the science of oceanography developed, M.B. Deacon the atmosphere and the ocean, H. Charnock the role of the ocean circulation in the changing climate, N.C. Wells et al ocean weather - eddies in the sea, K.J. Richards and W.J. Gould observing oceans from space, I.S. Robinson and T. Guymer marine phytoplankton blooms, D.A. Purdie snow falls in the open ocean, R.S. Lampitt the evolution and structure of ocean basins, R.B. Whitmarsh et al slides, debris flows and turbidity currents - slope failure and sedimentation, D.G. Masson et al mid-ocean ridges and hydrothermal activity, C.R. German et al the ocean - a global chemical system, J.D. Burton the marine carbonate system, M. Varney a walk on the deep side - animals in the deep sea, P.A. Tyler et al light, colour and vision in the ocean, P.J. Herring ocean diversity, M.V. Angel adaptation to life in estuaries, salt marshes, lagoons and coastal waters, A.O.M. Lockwood et al artificial reefs, A. Jensen and K. Collins scientific diving, J. Mallinson et al marine instrumentation, G. Griffiths and S.A. Thorpe the sea floor - exploring a hidden world, P. Riddy and D.G. Masson ocean resources, C. Summerhayes waste disposal in the deep ocean, M.V. Angel. Glossaries: the geological time scale SI units some common SI units some useful values some commonly used words and depths (depth zones, plankton, bacteria and marine animals).
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 1.000 | 0.999 |
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; both teacher heads agree on what is shown here.
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".