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Record W2130039621 · doi:10.1080/13887890.2005.9748244

Landscape variation in the larval density of a bromeliad-dwelling zygopteran,<i>Mecistogaster modesta</i>(Odonata: Pseudostigmatidae)

2005· article· en· W2130039621 on OpenAlexafffund
Diane S. Srivastava, Michael C. Melnychuk, Jacqueline T. Ngai

Bibliographic record

VenueInternational Journal of Odonatology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaInternational Dragonfly Fund
KeywordsOdonataBiologyEcologyLarvaAbundance (ecology)HabitatSecondary forestDragonfly

Abstract

fetched live from OpenAlex

In the premontane rain forests of northwest Costa Rica, patches of secondary forest can contain high densities of large Vriesea spp. bromeliads. Such patches contain an average of 6,470 ± 1,080 (s.e.) larvae ha-1 of the bromeliad-dwelling pseudostigmatid, Mecistogaster modesta, ca 3 6× higher than larval densities that we previously reported for adjacent primary forest.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.217
Teacher spread0.208 · 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

Citations23
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of OdonatologySame topicFreshwater macroinvertebrate diversity and ecologyFrench-language works237,207