Quantitative foraminiferal and palynomorph biostratigraphy of the Paleogene in the southwestern Barents Sea
Bibliographic record
Abstract
The stratigraphic distribution of both foraminifera and dinoflagellate cysts is recorded from the \nPaleocene to Eocene Torsk Formation in 12 petroleum exploration wells drilled in the southwestern \nBarents Sea. The foraminiferal assemblages are wholly agglutinated, and are referred to outer shelf to \nmiddle bathyal environments. A quantitative analysis of biostratigraphic events, mainly last \noccurrences (first downhole occurrences), is performed by means of the Ranking and Scaling (RASC) \nprogram. This procedure combined with conventional stratigraphic treatment has enabled us to \nestablish the most likely order of microfossil events, and to propose a new quantitative zonal scheme \nfor the southwestern Barents Sea. \nIn the studied wells the following six zones and subzones are distinguished (in ascending order): \nBSP 1, Psmmosphaera fusca – Hyperammina rugosa, late early to early late Paleocene; BSP 2, \nSpiroplectammina spectabilis early late Paleocene; BSP 3A, Reticulophragmium pauperum, middle late \nPaleocene; BSP 3B, Haplophragmoides aff. eggeri, latest Paleocene; BSP 4, Spiroplectammina navarroana, \nearliest Eocene; BSP 5, Reticulophragmium amplectens, early to middle Eocene. Owing to the \noccurrence of cosmopolitan deep-water agglutinated foraminifera, the new zonal scheme compares \nwell with previous zonations developed for the Paleogene of the mid-Norwegian shelf, the North Sea \nand Labrador Shelf.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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; 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".