Bibliographic record
Abstract
Gene flow from domesticated plants to free-growing relatives was a rather trivial issue before the advent of transgenic crops.Gene flow into crops was relatively more important, especially to plant breeders trying to introduce new genes in a crop, or to breeders and seed growers wanting to ensure the genetic purity of a cultivar.Genes can now be transferred from bacteria, or potentially any plant or animal species into crops and so, crop to weed gene flow is not so trivial anymore.What if these transgenes can persist in the environment?Anyone interested in this biosafety issue will soon realize that potential gene flow from crops is highly variable depending on the crop species and the presence of wild relatives where the crop is currently cultivated.While information on specific crops abounds, especially in scientific journals, most reviews that include multiple crops are published as regulatory reports and focus on crops grown in developed countries.The main objective of this book was to compile information on relationships between cultivated crops and their wild relatives in order to promote the conservation and utilization of crop genetic resources.Therefore, crops uncommon in developed countries but grown in areas of high biodiversity are included.Andersson and de Vicente, have worked and collaborated with multiple institutions and scientists around the world (Costa Rica, Germany, Colombia, USA and Italy, to name a few) to write this review.It is a good reference source, especially for regulators and policymakers, but also of interest to breeders, plant evolutionists, ecologists, conservationists, agronomists and botanists.The book allows the rapid assessment of gene flow potential by crop (each chapter from 2 to 22 focuses on a single crop) and by geographical location (world maps are presented at the end of the book).Each crop is introduced with a nice picture of its inflorescence.Chapters are in alphabetical order according to crop common name.Crop names are also found at the bottom right of odd pages, providing a simple index that allows rapid consultation.Chapter one outlines the importance of crop diversity and gene flow, as more and more genetically modified (GM) crops are planted.The authors define terms such as: gene flow, hybridization, introgression and ecological effects of introgression.Chapter two essentially describes the methodology for selecting and gathering the information.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".