Recent enhancements in ScaleNet: a queriable systematic database of the scale insects of the world (Hemiptera: Coccoidea)
Bibliographic record
Abstract
A number of changes have been implemented in ScaleNet since it was last discussed in 1998 at the International Symposium on Scale Insect Studies. These changes include addition of databases on the following 18 families: Aclerdidae, Beesoniidae, Carayonemidae, Cerococcidae, Dactylopiidae, Grimaldiellidae, Halimococcidae, Inkaidae, Jersicoccidae, Kermesidae, Kerriidae, Kukaspididae, Labiococcidae, Lecanodiaspididae, Micrococcidae, Phenacoleachiidae, Phoenicococcidae, and Stictococcidae making a total of 23 families on line. The bibliographic file has grown from 11,000 to over 14,700 references and a system has been developed to look for variant spellings of author names. A new query has been added that allows a search for a string of letters in a species epithet and very soon a section on on invasive species will be added. The "Scales in a Region/Country/Subunit Query" now allows a search for all of the species in a zoogeographic region, country, or country subunit in a particular scale family or genus. The "Hosts, Natural Enemies and Associates of a Scale Query" allows a search for all of the species that are found on a specified host, have specified natural enemies, or have specified associates in a particular scale family or genus. Significant progress has been achieved on the armored scale, margarodid, and asterolecaniid databases.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.027 |
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".