10.1016/0967-0653(96)87086-4
Bibliographic record
Abstract
Regeneration of silicon on mixing in the Bay of Bengal have been computed from six water masses [Bay of Bengal low saline water (BBLS), Bay of Bengal subsurface water (BBSS), northern southeast high salinity water (NSEHS), north Indian intermediate water (NIIW), Indonesian throughflow water (ITW) and Antarctic bottom water (AABW)]. The distribution of watermass fractions showed that BBLS with a maximum of 80-90% in the 40-60 m depth range and BBSS with 50% in the 150-300 m depth range are prominant. In the intermediate layers, NIIW shows a maximum percentage of 40% in 250-700 m depth region while ITW shows a maximum of 60% in 800-1000 m depth region. The deeper layers (below 3000 m) are predbminantly occupied by AABW with a maximum of 70%. Silicon regeneration consequent upon watermass mixing has been worked out based on the characteristics of silicon for individual watermass.
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) | 0.998 | 0.995 |
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".