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Record W6906136540 · doi:10.15482/usda.adc/1173245

ScaleNet: Scale Insects (Coccoidea) Database

2015· dataset· en· W6906136540 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2015
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCoccidaeDiaspididaeCreaturesScale (ratio)Scale insectAgricultureService (business)

Abstract

fetched live from OpenAlex

The objective of this database is to provide comprehensive information on the scale insects (Coccoidea) of the world, of which there are about about 7,800 species. Scale insects vary dramatically in their appearance from very small organisms (1-2mm) that occur under wax covers (some look like oyster shells), to shiny pearl-like objects (about 5mm), to creatures covered with mealy wax. They spend most or all of their lives feeding on plants and are primarily important as plant pests in greenhouses, backyards, and on fruit trees. Scale insects damage millions of dollars worth of food, ornamental, fiber and greenhouse crops each year. Until ScaleNet, information about the pests was buried in thousands of scientific journals and books, making it difficult for the average person to locate. The Agricultural Research Service developed ScaleNet with colleagues in Israel and Canada. It will allow anyone to locate every scale insect that experts over the centuries have found and named. Through keyword searches and other queries, ScaleNet provides comprehensive information including the insects' biology, classification, naming history, distribution, plant hosts, economic importance, controls and scientific literature about them. Currently, information can be retrieved for 49 families, namely Aclerdidae (grass scales), Albicoccidae, Arnoldidae, Asterolecaniidae (pit scales), Beesoniidae, Burmacoccidae, Callipappidae, Carayonemidae, Cerococcidae (ornate pit scales), Coccidae (soft scales), Coelostomidiidae, Conchaspididae (false armoured scales), Dactylopiidae (cochineal scales), Diaspididae (armoured scale insects), Electrococcidae, Eriococcidae (felt scales), Grimaldiellidae, Grohnidae, Halimococcidae, Hammanococcidae, Inkaidae, Jersicoccidae, Kermesidae (gall-like scales), Kerriidae (lac scales), Kukaspididae, Kuwaniidae, Labiococcidae, Lebanococcidae, Lecanodiaspididae (false pit scales), Lithuanicoccidae, Marchalinidae, Margarodidae (ground pearls), Matsucoccidae (bast scales), Micrococcidae, Monophlebidae, Ortheziidae (ensign scales), Pennygullaniidae, Phenacoleachiidae, Phoenicococcidae (date scales), Pityococcidae, Pseudococcidae (mealybugs), Putoidae, Rhizoecidae, Serafinidae, Steingeliidae, Stictococcidae, Stigmacoccidae, Weitschatidae, and Xylococcidae. The Reference database of ScaleNet includes about 25,000 references, the majority of which have been published since Linnaeus (1758). However, it also contains several pre-Linnean publications that are relevant to the nomenclature and systematics of the Coccoidea. Funding information to 2015: Originally ScaleNet was funded by United States-Israel Binational Agricultural Research and Development Fund (BARD) (Grant Numbers IS-2423-94 and IS-2605-95). Additional funding was supplied by the Systematic Entomology Laboratory to fund an additional computer, and two contracts to enter bibliographic information. The Agricultural Research Service of the USDA provided funding for a technical information specialist. Future grant funding to sustain ScaleNet to be added when available.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.187
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.5510.738

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.

Opus teacher head0.117
GPT teacher head0.328
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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