Bibliographic record
Abstract
Wild berries are a rich source of various biologically active substances. This paper focuses on the investigation of most common Russian forest berries on the total content and profile of anthocyanins, proanthocyanidins and total antiradical and antioxidant activity in 1-diphenyl-2-picrylhydrazyI (DPPH) and ferric reducing antioxidant power (FRAP) tests. Among berries analyzed were representatives of Ericacea family – bilberry, blueberry, crowberry, lingonberry, cranberry (V. oxycoccus and V. macrocarpon), of Caprifoliaceae family – honeysuckle, elderberry, vilburnum and Rosaceae family – chokeberry and saskatoon berry. Total anthocyanins were determined by pH-differential spectrophotometry, anthocyanin profile – by HPLC-TOF-mass-spectrometry, sum of proanthocyanidins – was estimated by colorimetry after butanol-hydrochloric acid hydrolysis. More than 100 samples of berries were selected from the northwestern and northern regions of the European part of Russia and western Siberia. The obtained data on the specific composition of anthocyanins and antioxidant properties of domestic berries are relevant to assess their potential effectiveness as a raw material for biological active food supplements and fortified foods and to develop criteria for authenticity and nutritional value of the berry raw materials.
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.
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 | 0.000 |
| 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".