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Record W6940324227 · doi:10.7479/87tp-gr35

Non-invasive 3D visualization of the sponge-inhabiting barnacle Acasta sulcata (Crustacea: Cirripedia: Balanomorpha) from the Moluccas, Indonesia

2020· other· en· W6940324227 on OpenAlexaff

Bibliographic record

VenueMuseum für Naturkunde Berlin - Leibniz-Institut für Evolutions- und Biodiversitätsforschung · 2020
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsMinnow Environmental (Canada)
Fundersnot available
KeywordsBarnacleStudioPebbleVisualizationChristian ministryVolume rendering

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.012
GPT teacher head0.232
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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