Identification and documentation of herbicide resistance
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
Proactive herbicide resistance management programs rely upon early detection of resistant populations and knowledge of which combinations of weed and herbicide are prone to the development of resistance. Annual weeds that are prolific seed producers, genetically diverse, and repeatedly exposed to a single herbicide mode of action, are prone to rapid development of resistance. When resistance is suspected, seed samples are collected and evaluated using a whole plant bioassay. Whole plant bioassays are conducted underfield, growth room, or Petri dish conditions. Complete dose response curves for the suspected resistant and a reference susceptible population are used to verify resistance. Bioassay, conducted in growth rooms, is the most reliable method for identification of new cases of herbicide resistance. Bioassays, based on the biochemical detection of a single mechanism of resistance, are not reliable for screening for new occurrences of resistance.
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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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