Bibliographic record
Abstract
Theinuenceoftheverticalvariabilityofsuspendedmatter C(z)withintheoptical penetration layer on the reectanceR(�) over the sea surface in the southern BalticandtheGulfofGda«skwereanalysed.UsingGordonandClark'smodelthe value of reectanceR(620), taken to be representative of AVHRR channel 1, was calculated. Various vertical seston proles obtained after previous analysis of real distributions of suspended matter in the surface layer of the sea were taken to be inputparameters. The variability of vertical seston distribution on R(620) was found to be neg- ligible except when the surface concentration exceeded 8 mgdm 3 and rapidly decreased with depth. In order to estimate the seston content of the sea surface layer using optical remote sensing methods, the best results should be achieved whencomparingreectancewiththeoptically-weightedco ncentration'denedby Gordon and Clarke (1980). Except in areas close to river mouths and other ter- restrialsourcesofsestonintheBaltic,theverticalvariabilityofsuspendedmatter within the optical penetration layer (typically a few metres) is rather small. This meansthatsurfacemeasurementsofsestonconcentrationcanbeusedtocalibrate the C= f(R)relationship. Using AVHRR channel 1 data it is possible in the southern Baltic to record surfacechanges insuspendedmatterconcentrationoftheorder of0.5mgdm 3 .
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.003 |
| Insufficient payload (model declined to judge) | 0.992 | 0.993 |
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; the direct Gemma label and the distilled Codex classifier 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".