Measure of agreement between experts on apple damage assessment
Bibliographic record
Abstract
Although damage evaluation is an important and frequent exercise in economic entomology, there are no quantitative studies on inter-rater agreement of experts. In this experiment conducted during the 50 th New York, New England and Canadian Pest Management Conference, four teams of experts independently estimated the damage on 200 apples at harvest. The participants identified 22 types of damage caused by insects, 8 by diseases, and 8 related to other causes. For each type of damage an average measure of agreement was calculated. The lowest average agreements were found in plum curculio ( Conotrachelus nenuphar ) [Coleoptera : Curculionidae] damage (71.8%), tarnished plant bug ( Lygus lineolaris ) [Hemiptera : Miridae] damage (83.2%), and by early lepidoptera damage (87.1%). The usefulness of inter-rater agreement experiments is discussed in the context of many situations pertaining to crop protection.
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 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".