Assessing mold growth severity on various textiles: comparative analysis of inoculum densities and fungal strains
Bibliographic record
Abstract
Abstract Mold growth on textiles during overseas shipping poses significant economic and health risks, necessitating a comprehensive understanding of fungal contamination dynamics. This study evaluated textile susceptibility to fungal contamination during transit by examining growth patterns, onset times, and determining minimum fungal densities for visible mold growth. Inoculations of six fungal strains (individual and pooled) were conducted at inoculum densities ranging from 102 to 106 spores/ml on various textile materials. The study comprised two phases: pilot growth (PG, with glucose) and Simulated Shipping Conditions (SSC, without glucose). PG yielded mycelial mats on textiles for all fungal strains except Penicillium citrinum and Stachybotrys chartarum. SSC exhibited variable susceptibilities, with cotton and suede highly susceptible and polyester, imitation suede, and polyurethane notably resistant to mycelial growth. Minimum fungal densities for visible mold growth were established for each textile based on SSC. The findings reveal distinct fungal susceptibilities among textiles, influenced by material composition and structure. Consistent growth on certain textiles at lower fungal densities highlights the need for targeted preventive measures. This research provides crucial insights for the manufacturing and shipping industries, guiding the development of effective mold prevention strategies and establishment of contamination limits during overseas transport.
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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) | 0.000 | 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) | 0.001 | 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".