Plants: An International Scientific Open Access Journal to Publish All Facets of Plants, Their Functions and Interactions with the Environment and Other Living Organisms
Bibliographic record
Abstract
Plants are one of the two major groups of living organisms that are an essential entity to the function of the biosphere. Plants can be found in all known parts of the earth, in all shapes and sizes. They include the green algae, mosses, ferns, vines, grasses, bushes, herbs, flowering plants and trees. Although some plants are parasitic, most produce their own food through photosynthesis. Most plants initiate from a seed. The importance of plants in the food chain dates back to ancient times. The first humans gathered wild plants for food. As settlements developed, food crops were cultivated, leading to selection of high-yielding cultivated varieties to feed the growing populations. Unlike plants, humans and other animals are unable to manufacture their own food. Therefore, they are dependent, directly or indirectly, on plants. Plants are found in natural ecosystems such as rain forests, and also in agricultural areas and urbanized settings. They are an essential part of our daily lives providing food, clean air, and important ecosystem functions. The study of plants and their function could be considered the most complex of interactions. From the time a seed germinates, it goes through a myriad of physiological processes that can be closely studied using modern tools and molecular biological methods. An open access journal such as Plants will give millions of readers access to that information around the world.
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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.053 | 0.047 |
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".