Non-invasive 3D visualization of the sponge-inhabiting barnacle Acasta sulcata (Crustacea: Cirripedia: Balanomorpha) from the Moluccas, Indonesia
Bibliographic record
Abstract
We present a digital reconstruction (video) of non-invasive microCT scans of barnacle specimens (Acasta sulcata) embedded in their sponge host (Spongia sp.) from the Indonesian island Saparua, Moluccas (for details see Pitriana et al. 2020). The sponge specimen, which was supposed to host barnacles, was subjected to micro-tomographic analysis at the Museum für Naturkunde Berlin, using a Phoenix nanotom X-rays tube at 90 kV and 150 µA, generating 1440 projections. The specimen was fixed with foam in a sealed plastic tube in an ethanol-saturated atmosphere. Cone beam reconstruction was performed using the phoenix/x-ray datos/x version 2.3.3 software (GE Sensing and Inspection Technologies GmbH). Effective voxel size, i.e. resolution in three-dimensional space, is 13.33 µm. Data were visualized in VG Studio Max, version 3.1. In the video, barnacles are shown as an isosurface in red color, the surrounding sponge tissue as volume rendering in grey color (original length of sponge host 10 cm; length of barnacles approx. 2.5 mm). This study is part of Pipit Pitriana’s PhD project funded by the Ministry of Research, Technology and Higher Education, the Republic of Indonesia within the Program for Research and Innovation in Science and Technology (RISET-Pro), World Bank Loan No. 8245-ID. We thank Kristin Mahlow and Prof. Johannes Müller for their support at the MfN Berlin and Prof. Frank Riedel (FU Berlin) for his general support.
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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 | 0.000 |
| 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) | 0.002 | 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".