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Record W7061349680

Relative effects of landscape and local habitat characteristics on grassland songbird abundance and occurrence in southwestern Manitoba

2016· dissertation· en· W7061349680 on OpenAlexaffabout

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
Fundersnot available
KeywordsNucleofectionHyporeflexiaGestational periodDiafiltrationExclosureHemopericardium
DOInot available

Abstract

fetched live from OpenAlex

I investigated the relative effects of grassland cover and fragmentation per se, and the relative influence of landscape and local habitat characteristics on grasslands songbirds in the moist mixed-grass prairies of Manitoba. In 2013, 361 avian point counts were conducted across 47, 2.4-km radii landscapes in the southwest part of the province. I used an information-theoretic approach to rank and select models describing effects of landscape and local-scale habitat variables on grassland songbird abundance and occurrence. Overall, my results indicate that grassland amount, fragmentation and quality, and matrix composition had relatively small and variable effects on grassland songbird abundance and occurrence, but that abundance of obligate species when pooled showed a strong negative response to grassland fragmentation. While fragmentation through edge effects may contribute to obligate species declines, my results suggest that these factors alone are unlikely to explain ongoing declines of grassland birds in southwestern Manitoba.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.613

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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
Published2016
Admission routes2
Has abstractyes

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