MétaCan
Menu
Back to cohort
Record W6929535997 · doi:10.5061/dryad.6g206

Data from: Tracking the history and ecological changes of rising double-crested cormorant populations using pond sediments from islands in eastern Lake Ontario

2015· dataset· en· W6929535997 on OpenAlexaffabout

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2015
Typedataset
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsUniversity of OttawaEnvironment and Climate Change CanadaQueen's University
Fundersnot available
KeywordsCormorantPopulationVegetation (pathology)Biomass (ecology)SedimentHabitatCompetition (biology)

Abstract

fetched live from OpenAlex

In the Laurentian Great Lakes region, the double-crested cormorant (Phalacrocorax auritus) has seen a thousand-fold population increase in recent decades. These large colonies of birds now often conflict with socioeconomic interests, particularly due to perceived competition with fisheries and the destruction of terrestrial vegetation in nesting habitats. Here we use dated sediment cores from ponds on islands in eastern Lake Ontario that receive waste inputs from dense colonies of cormorants and ring-billed gulls (Larus delawarensis) to chronicle the population rise of these species and assess their long-term ecological impacts. Modern water chemistry sampling from these sites reveals drastically elevated nutrient and major ion concentrations compared to reference ponds not influenced by waterbirds. Geochemical tracers in dated sediment cores, particularly δ15N and chlorophyll-a concentrations, track waterbird influences over time. Fossil diatom assemblages were dominated by species tolerant of hyper-eutrophic and polluted systems, which is in marked contrast to assemblages in reference sites. In addition to establishing long-term ecological impacts, this multi-proxy paleoecological approach can be used to determine whether islands of concern have been long-term nesting sites or were only recently colonized by cormorant or ring-billed gull populations across the Great Lakes, facilitating informed management decisions about controversial culling programs.

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: Dataset · Consensus signal: none
Teacher disagreement score0.172
Threshold uncertainty score0.347

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.193
GPT teacher head0.333
Teacher spread0.140 · 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
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

Citations0
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueData Archiving and Networked Services (DANS)Same topicJapanese History and CultureFrench-language works237,207