Laevidentalium wiesei Sahlmann, 2012 (Scaphopoda: Dentaliida: Laevidentaliidae) – tomographic datasets
Bibliographic record
Abstract
This file collection encompasses x-ray tomographic datasets for two ethanol-preserved specimens of the abyssal scaphopod Laevidentalium wiesei Sahlmann, 2012 housed in the malacological collection of the Senckenberg Research Institute and Natural History Museum Frankfurt (Frankfurt am Main, Germany; catalogue numbers SMF 373200 and SMF 366426). The animals were collected in 2022 by the SO293 (AleutBio) expedition of research vessel Sonne to the Aleutian Trench and the abyssal Bering Sea (Brandt 2022) and used in the redescription of this poorly known species. For individual SMF 366426, a VGSTUDIO MAX volume (can be opened in the free myVGL viewer) and a 3D surface model are available. Methods: Shell shape and soft body anatomy were studied by micro-computed tomography (µCT), using a Werth TomoScope XS Plus CT scanner with the following settings [scan of SMF 373200/scan of SMF 366426]: acceleration voltage 60/80 kV, emission current 180/200 µA, exposure time 666 ms, voxel size 6.29/21.81 µm, number of images per revolution 2,000/1,000. Prior to scanning, specimens had been contrasted in a solution of 0.3% phosphotungstic acid and 3% dimethyl sulfoxide in 95% ethanol (Senckenberg Ocean Species Alliance (SOSA) et al. 2024) for 27 days. The 3D shell reconstruction of SMF 366426 was obtained by first cropping the raw tomographic dataset in Avizo3D (v. 2024.1; Thermo Fisher Scientific) and postprocessing the resultant file in VGSTUDIO MAX (v. 2024.3; Volume Graphics). References Brandt, A. (2022). SO293 AleutBio (Aleutian Trench Biodiversity Studies). Cruise Report/Fahrtbericht, Cruise No. SO293, 24.07.2022 – 06.09.2022, Dutch Harbor (USA) – Vancouver (Canada). 209 pp. https://doi.org/10.48433/cr_so293 Senckenberg Ocean Species Alliance (SOSA), Brandt A., Chen C., Engel L., Esquete P., Horton T., Jażdżewska A.M., Johannsen N., Kaiser S., Kihara T.C., Knauber H., Kniesz K., Landschoff J., Lörz A.-N., Machado F.M., Martínez-Muñoz C.A., Riehl T., Serpell-Stevens A., Sigwart J.D., Tandberg A.H.S., Tato R., Tsuda M., Vončina K., Watanabe H.K., Wenz C., Williams J.D. (2024). Ocean Species Discoveries 1–12 — A primer for accelerating marine invertebrate taxonomy. Biodiversity Data Journal 12: e128431. https://doi.org/10.3897/BDJ.12.e128431
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.050 |
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".