Bibliographic record
Abstract
Abstract Douglas fir is a native species of western North America, China, Taiwan, and Japan. Its high quality lumber is in demand throughout the world and therefore, breeding objectives include improvement of economic value and adaptability to biotic and abiotic stresses. Similar to other conifers, the reproductive cycle of Douglas fir is lengthy (17 months) and the time from pollination to cone maturity is 6 months. The pollination mechanism is unique in that pollen granule takes 9 weeks to germinate and elongate. The most efficient method for improving economic value is by capturing multiple desirable traits in a single individual and propagation of this genotype via somatic embryogenesis. Presently, the main incentives for transgenic breeding are to provide methods to confer insect and fungal resistance, and the temporary transfer of genes that may induce somatic embryogenesis. Thus far, experiments with Agrobacterium ‐mediated transformation have identified several strains that effectively transform Douglas‐fir tissues, and stem woodiness, plant age, and plant defense mechanisms have been identified as factors that influence success rate. Electroporation and microprojectile bombardment have also been investigated and cytokinin pulsing was shown to improve transformation efficiency. The use of endogenous and/or tissue‐specific promoters will be useful in enhancing and ontrolling transgene expression.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.039 | 0.020 |
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".