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Record W6910842778 · doi:10.5063/f1zc8145

Data from: Drought alters the trophic role of an opportunistic generalist in an aquatic ecosystem, Oecologia

2019· dataset· en· W6910842778 on OpenAlexaff

Bibliographic record

VenueUC Santa Barbara · 2019
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPredationTrophic levelMicrocosmDesiccationGeneralist and specialist speciesIntraguild predationInvertebrate

Abstract

fetched live from OpenAlex

Data from Experiment 1 and Experiment 2 in Oecologia by Amundrud and Srivastava. We performed two microcosm experiments in which we factorially manipulated water level and predation by tipulids, and measured the effects on mosquito and chironomid larvae. The experiments differed in whether high water was contrasted with low or no water, allowing us to distinguish between the effects of desiccation stress (no water) and increased encounter rates due to compression of habitat or reductions in prey mobility (low and no water). We also included a caged tipulid treatment to measure any non-consumptive effects. As well as directly reducing prey survival, reductions in water level indirectly decreased chironomid and mosquito survival by altering the trophic role of tipulids. Our results suggest that increased encounter rates with prey led to tipulids becoming predatory under simulated drought, as tipulids consumed prey under both low and no water. When water level was high, tipulids exerted negative non-consumptive effects on prey survival.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.071
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.024

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 head0.082
GPT teacher head0.324
Teacher spread0.241 · 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 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
Published2019
Admission routes1
Has abstractyes

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