Bibliographic record
Abstract
Welcome to the first issue of the seventh volume of the Plant Biotechnology Journal. It is difficult to believe that the journal is now six years old and that the Plant Biotechnology Journal has now published ~350 of the very best research and review articles in pure and applied plant sciences. Looking back at these articles I am pleased to report that many have been highly cited, with the very first ('The molecular analysis of leaf senescence – a genomics approach', Buchanan-Wollaston et al., Plant Biotechnology Journal, 1, 3–22, 2003) being cited 121 times. In 2008, the Plant Biotechnology Journal increased the number of annual issues from six to nine. This increase has proven to be a great success, in so much as it has enabled the editorial office to speed up the processing of manuscripts so that our average time from submission to first decision has been reduced from a respectable 24 days to just 21 days. The editorial team believes that this rapid turnaround is one of the primary reasons for the increased number of manuscripts submitted in 2008. However, unfortunately, this significant increase has also resulted in an increase in the number of manuscripts rejected; currently 75% of the manuscripts submitted to the Plant Biotechnology Journal are rejected at some point during the review process. In connection with the Plant Biotechnology Journal's high rejection rate, I am often asked by authors for advice on how to minimize the chance of rejection. In response, I have three simple pieces of advice: (i) only submit your best manuscripts to the Plant Biotechnology Journal, as only those manuscripts that include novel findings of biological significance will be accepted for review; (ii) provide the journal with concise manuscripts, in the correct format and free from grammatical and typographical errors; and (iii) be prepared to meet, in full, the requirements of both the reviewers and the handling editor. By meeting all of these criteria authors will considerably enhance the chances of their manuscript being published in the Plant Biotechnology Journal. In 2008, we at the Plant Biotechnology Journal were fortunate in being able to recruit Professor Malcolm Campbell from the University of Toronto to its editorial team. Professor Campbell is a leading authority on the molecular mechanisms that control plant architecture, including the regulation of those aspects of plant growth and development that are critical in architectural design. During 2009, the editorial team of the Plant Biotechnology Journal intends to publish several special issues covering topics of immediate interest to our readers. So far two special issues, one on biofuels and one on SNP development and high throughput genotyping, are planned. In addition, the editorial team is also interested in hearing from you our readers about titles for other possible special issues. Although worthwhile, publishing special issues is time consuming; hence, the editorial team would be interested in hearing from appropriately experienced researchers interested in co-editing specific special issues. Finally, plant researchers like all researchers are not immune from the socioeconomic factors that affect all of human kind. The last 12 months have seen the price of food commodities hit record highs only to drop rapidly as the various world economies slip into recession. Although such events are alarming and will unfortunately have numerous consequences, they should not blind us to the fact that the human race is running out of time and options. It is my personal view that the major problems facing the human race are a lack of resources, which are both food and fuel-based. As I suggested during my 2008 editorial, many of these problems can only be solved by the appropriate use of plant-based science and technology. Hence, in 2009 I look forward to seeing more papers published that use plant biotechnology to address such global issues.
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 | 0.003 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.348 | 0.236 |
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".