Bibliographic record
Abstract
`Marion' is the most important blackberry cultivar in the world, primarily due to its outstanding processing characteristics. Ideally, `Marion' could be enhanced via transformation while maintaining its fruit quality. As a successful in vitro regeneration is the prerequisite for genetic transformation, a series of experiments were conducted to optimize the conditions for in vitro regeneration for `Marion' blackberry. Parameters studied included types (three cytokinins: BA, kinetin, and zeatin; four auxins: IBA, IAA, NAA, and 2,4-D) and concentrations of plant growth regulators, explants (leaf and petiole), medium formulations (MS, WPM, and BMM), and the duration of TDZ pretreatment (3 to 6 weeks) of in vitro-grown stock plants. The highest shoot regeneration rate (65.7%) and highest number of shoots (5.1 shoots/explant) were obtained under the following conditions: stock plants were pretreated with TDZ (1 m m ) for 3 weeks, followed by leaf explants dark pretreatment for 1 week on the regeneration medium (WPM with 5 mM BA and 0. 5 m m IBA). After dark treatment, regeneration plates were placed under 16-h photoperiod at light intensity of ≈50 μmol·m -2 ·s -1 at 23 + 2 °C for 4 weeks.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".