Bibliographic record
Abstract
It is well known that there is a close relationship between physical and biological processes in the ocean. However, despite this knowledge, it is surprising that physical oceanography still plays a very modest part in some marine biological milieu. We therefore believe that there is a need to stimulate to more cooperation between physicists and biologists to prevent future marine scientific programs which suffer due to lack of cooperation. Lack of integration of physical oceanography in biological investigations often has economical reasons. Ecological field experiments are time consuming and costly and biologists are tempted to limit the physical oceanographic part to a minimum and make “a best guess” based on e.g. a few CTD-stations. Such data, however, tells usually next to nothing about the physical processes which are necessary to interpret the biological data in a satisfactory way. It is usually decisive that the physical data are sampled simultaneously with the biological data. This is especially important in areas with strong gradients where the processes take place on small time and space scales, e.g. in fronts, current shear, upwelling. The possibility of cooperation in field experiments has been facilitated in recent years. Work is in continous progress on the development of instruments which have improved the measuring technique and increased the efficiency of data sampling, which has therefore become considerably less time consuming than just a few years ago. Some of the biological data may today be collected with a coverage and resolution comparable with the best physical data. Also the development of ecological models (coupled hydrodynamical and biological models) have been an inspiration for cooperations.
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 | 1.000 |
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 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".