Three-dimensional reconstruction of high latitude bamboo coral via X-ray microfocus Computed Tomography
Bibliographic record
Abstract
The skeletons of long-lived bamboo coral (Family Keratoisididae) are promising archives for deep-water palaeoceanographic reconstructions as they can record environmental variation at sub-decadal resolution in locations where in-situ measurements lack temporal coverage. Yet, detailed three dimensional (3D) characterisations of bamboo coral skeletal architecture are not routinely available and non-destructive investigations into microscale variations in calcification are rare. Here, we provide high-resolution micro-focus computed tomography (µCT) data of skeletal density for two species of bamboo coral (Acanella arbuscula: 5 specimens, voxel size, 15 µm (central branch scans) and 50 µm (complete structure scan); Keratoisis sp.: 4 specimens, voxel size, 15 µm) collected from the Labrador Sea and Baffin Bay deep-water basins, Eastern Canadian Arctic. These data provide reference models useful for developing methods to assess structural integrity and other fine-scale complexities in many biological, geological, and industrial systems. This will be of wider value to those investigating structural composition, arrangement and/or composition of complex architecture within the fields and subdisciplines of biology, ecology, medicine, environmental geology, and structural engineering.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".