Weed seedling images of species common to Manitoba, Canada
Bibliographic record
Abstract
This dataset contains 34666 RGB-images taken from different angles and distances of weeds common in Manitoba. The imaged species common name, scientific name, and number of their images are: Echinochloa crus-galli Large Barnyard Grass 8621 Cirsium arvense Canada Thistle 4706 Brassica napus Volunteer Canola 6723 Taraxacum officinale Dandelion 4797 Persicaria spp. Smartweed 870 Fallopia convolvulus Wild Buckwheat 4165 Avena fatua Wild Oat 1218 Setaria pumila Yellow Foxtail 3566 Furthermore, this dataset contains a trained ResNet50 convolutional neural network model. It is trained to distinguish between monocots and dicots. A small collection of test datasets is included that can be used to measure the generalization capabilities of trained models. The single-plant dataset and all test-datasets are accompanied by a csv-file containing filenames with respective labels.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.028 |
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".