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Record W2104459806 · doi:10.3852/mycologia.97.2.312

Fungal melanin detection by the use of copper sulfide-silver

2005· article· en· W2104459806 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMycologia · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicmelanin and skin pigmentation
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMelaninBiologyStainingSilver stainHyphaCopperStainCell wallSulfideMicrobiologySodium sulfideBiochemistryMolecular biologyChemistryMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Silver-staining procedures were investigated for their effectiveness in identifying cell wall-based fungal melanins in live and fixed plastic embedded samples, particularly 1,8-dihydroxynaphthalene (DHN) based polyketide melanins. We developed a simple and reliable melanin-staining technique based on a silver accumulation method originally published for histological demonstration of heavy metal sulfides in mammalian tissues. Copper is bound to fungal melanin followed by formation of the copper sulfide at melanin sites in fungal cell walls, which then are amplified into vivid black stains using a silver enhancement step. The method demonstrates patterns of melanization in a range of fungal hyphae and is suitable for light and electron microscopy. Albino mutant fungi and normally nonmelanized fungi do not stain with the sulfide-silver technique. Mammalian melanocytes also were labeled by the technique, indicating its universality as a melanin probe.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.246
Teacher spread0.225 · 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