Cultivation of Agaricus blazei ss. Heinemann using different soils as source of casing materials
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
Commercial productivity of the Agaricus blazei mushroom is closely related to both the quality of the compost and the choice of soil to be used as a casing material. This study aims to evaluate Agaricus blazei's productivity using two compost formulations and three soils. The two compost formulations were (i) crushed sugarcane bagasse (Saccharum officinarum (L.)) and Coastcross hay (Cynidon dactylon (L.) Pers.), and (ii) crushed sugarcane bagasse (Saccharum officinarum (L.)) and corn husk (Zea mays L.); they were amended with wheat bran, lime, gypsum, superphosphate and urea. The casing materials were extracted from three soils classed as Rhodic Hapludox, Xanthic Hapludox, and Humic Haplaquox. The Rhodic Hapludox soil material was mixed with fragments of Eucalyptus charcoal in the proportion of 4:1. The compost was prepared during six weeks and thereafter heat treated during 48 h at the end of the composting period. The sugarcane bagasse:coast-hay compost was superior to the sugarcane bagasse: corn husk compost. The Rhodic Hapludox plus charcoal casing material showed to be a better casing material than either the Xanthic Hapludox and Humic Haplaquox soil materials. The choice of the soils where the casing material is taken is an important factor to the success of the Agaricus blazei mushroom cultivation.
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