Assembly theory applied to weed communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Community assembly is a branch of ecology that looks at how communities are assembled as they follow trajectories through time. A trajectory is controlled by biotic and abiotic constraints (filters) that act at multiple scales. From a total species pool, environmental and dispersal constraints control which species enter an ecological species pool. Within this pool, internal dynamics determine which of these species becomes part of the extant community. Environmental filters act by removing species that lack specific traits. Thus, traits are filtered, and with them, species. In this paper, we present the basic ecological theory of community assembly and address how it can be used in conjunction with a trait-based approach to understand and possibly predict how weed community structure changes in response to imposed filters such as tillage or crop rotation. Weed ecologists have struggled with the need to place our practical knowledge of agriculture and weeds into a broader theory, and there have been many calls to integrate ecology with agronomy and weed science. Community assembly might be one way to do so.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it