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Record W6911212860 · doi:10.5281/zenodo.10167001

Atheta (Lamiota) keeni Casey 1910

2023· article· en· W6911212860 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicColeoptera Taxonomy and Distribution
Canadian institutionsNatural Resources CanadaAgriculture and Agri-Food CanadaCanadian Forest Service
Fundersnot available
KeywordsLitterUnderstoryPlant litterTable (database)ConfusionMoss

Abstract

fetched live from OpenAlex

48. Atheta (Lamiota) keeni Casey (Illustrations in Klimaszewski et al. 2020, 2021), Table 1 References. Casey 1910. Gusarov 2003. Klimaszewski and Winchester 2002a (as L. vasta). Klimaszewski et al. 2020, 2021. Distribution. Nearctic, transcontinental in Canada, reported from A/S (Klimaszewski et al. 2021). Canada:AB, BC. USA: AK, NH (NSR), OR. Collection and Habitat data. In NH a single female was captured in a FIT in June at a site near the border with Quebec. In AK found in forest litter of Alnus, Verathrum, and ferns (Klimaszewski et al. 2021). In BC found in a transition zone of Sitka spruce, in dung and carrion, in Alnus litter, in moss, fern, and Amelanchier litter at edge of upland pond, and in moss and leaf litter near a creek; in AB found in a Douglas fir and lodgepole pine stand with aspen and birch understory (Klimaszewski et al. 2021). Material. USA, New Hampshire, Coos Co.: 1 mi NE East Inlet Dam, 12–24.VI.1996, D.S. Chandler, FIT, 1 female. Comments. The record from NH should be consider as a tentative one because it is based only on single female specimen, and there is a possibility of confusion with some other species.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.200

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0600.027

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.

Opus teacher head0.050
GPT teacher head0.227
Teacher spread0.177 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes2
Has abstractyes

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