Bibliographic record
Abstract
Isoflavonoids are biologically active plant natural products synthesized via general phenylpropanoid pathway. They accumulate predominantly in plant species belonging to family Leguminosae. Isoflavonoids play numerous roles in the interaction between plants and environment, where they act as inducers of nodulation genes during symbiosis between legumes and Rhizobium bacteria (Ferguson & Mathesius 2003, Phillip 1992) and also function as precursor molecules for the production of phytoalexins during plant-microbe or plantinsect interactions (Aoki et al. 2000, Dixon 1999, Dixon & Ferreria 2002). Many epidemiological and clinical trials have suggested a positive role for isoflavonoids in human health and nutrition (Aerenhouts et al. 2010, Cederroth & Nef 2009). The core isoflavones have structural similarity to beta-estradiol (Fig. 1) and possess affinity for oestrogen receptors (Molteni et al. 1995). Due to their structural resemblance with beta-estradiol, isoflavonoids have been associated with chemo-preventive activities against hormone dependent cancers such as breast cancer and post-menopausal ailments (Dixon 2004, Limer & Speirs 2004). Research data over the past decade suggests that the dietary intake of isoflavonoids may also be associated with many additional health benefits such as reduction of risk of cardiovascular diseases, osteoporosis, loss of bone mass intensity (reviewed in Messina 1999, Rochfort & Panozzo 2007, Zhang & Yu 2009). Due to these pharmaceutical and nutraceutical properties associated with isoflavonoids and their use in functional foods, there is a growing interest in these compounds and the plants that produce them.
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 | 0.000 | 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) | 0.001 | 0.001 |
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".