A global food plant dataset for wild silkmoths and hawkmoths and its use in documenting polyphagy of their caterpillars (Lepidoptera: Bombycoidea: Saturniidae, Sphingidae)
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
BACKGROUND: Herbivorous insects represent a major fraction of global biodiversity and the relationships they have established with their food plants range from strict specialists to broad generalists. Our knowledge of these relationships is of primary importance to basic (e.g. the study of insect ecology and evolution) and applied biology (e.g. monitoring of pest or invasive species) and yet remains very fragmentary and understudied. In Lepidoptera, caterpillars of families Saturniidae and Sphingidae are rather well known and considered to have adopted contrasting preferences in their use of food plants. The former are regarded as being rather generalist feeders, whereas the latter are more specialist. NEW INFORMATION: To assemble and synthesise the vast amount of existing data on food plants of Lepidoptera families Saturniidae and Sphingidae, we combined three major existing databases to produce a dataset collating more than 26,000 records for 1256 species (25% of all species) in 121 (67%) and 167 (81%) genera of Saturniidae and Sphingidae, respectively. This dataset is used here to document the level of polyphagy of each of these genera using summary statistics, as well as the calculation of a polyphagy score derived from the analysis of Phylogenetic Diversity of the food plants used by the species in each genus.
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 | 0.001 |
| 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