Molecular assessment of fungi in “black spots” that deface murals in the Takamatsuzuka and Kitora Tumuli in Japan: <i>Acremonium</i> sect. <i>Gliomastix</i> including <i>Acremonium tumulicola</i> sp. nov. and <i>Acremonium felinum</i> comb. nov
Bibliographic record
Abstract
Unidentified black spots (or stains) appeared on the plaster walls of the Takamatsuzuka and Kitora Tumuli in the village of Asuka, Nara Prefecture, Japan. Public attention was drawn to the biodeterioration of the colorful 1,300-year-old murals. A total of 46 isolates of Acremonium sect. Gliomastix were obtained from various samples (mainly black spots) of the Takamatsuzuka Tumulus (TT) (sampling period, May 2004–December 2006) and the Kitora Tumulus (KT) (June 2004–May 2007). These isolates were assignable to four known taxa and a new species in the ‘series Murorum’ sensu W. Gams as inferred from the integrated analysis of phenotypic and genotypic (i.e., ITS and 28S rDNA-D1/D2 sequences) characters: these were Acremonium masseei, A. murorum, A. felinum comb. nov. with the neotype designation, A. polychromum, and A. tumulicola sp. nov., which have been accommodated in the validated series Murorum in the section Gliomastix. The black spots on the murals of the TT and KT were caused mainly by A. masseei and A. murorum, respectively.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".