SPECIATION OF PHOSPHORUS IN MANURE- AND INORGANIC FERTILIZER-AMENDED SASKATCHEWAN SOILS
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.
Bibliographic record
Abstract
3D food printers facilitate novel customization of the physicochemical properties of food. This study aimed to investigate the impact of storage conditions on the inactivation of the human norovirus surrogate, Tulane virus (TuV), within 3D printed foods. TuV-inoculated protein cookie food ink (∽ 4 log PFU/g) was distributed into 18 3D food printer capsules (50 g each); half immediately underwent extrusion. Storage of the capsules and printed food products at 20 °C (0, 6, 12, and 24 h), 4 °C (0, 1, 3, and 5d), and - 18 °C (0, 1, 3, and 5d) was completed before analysis for TuV via plaque assays in addition to aerobic plate count, yeast and mold counts, and pH and water activity (a<sub>w</sub>) measurements. A significant 3-way interaction effect was observed between time, temperature, and storage method (capsule/print) (p = 0.006). Significant findings include: (1) A greater reduction in virions was observed in capsules after 24 h at 20 °C and (2) a substantial reduction in virions at 4 °C from day 0 to day 1 was observed, independent of storage method. Microbial indicators remained steady across temperatures, with storage temperature significantly impacting pH and a<sub>w</sub>. A significant two-way interaction effect (p = 0.006) was found between microorganism type (yeast/aerobic counts) and temperature. This research seeks to provide insights for the food industry and regulatory bodies in crafting guidelines for the safe storage and handling of 3D printed foods and inks.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it