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Record W7018697500

Effects of natural gas well development on songbird reproductive success in mixed-grass prairies of southeastern Alberta

2014· dissertation· en· W7018697500 on OpenAlexfundaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCenovus Energy
KeywordsNucleofectionGestational periodHyporeflexiaTSG101DiafiltrationProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Grassland songbird populations have experienced declines due to habitat loss. In Canada, gas well development continues to fragment and disturb prairie habitat. From 2010-2012, I monitored a total of 374 nests in mixed-grass prairie located in southeastern Alberta. I estimated the probabilities of nesting success relative to gas well infrastructure to test for effects on reproductive success. There was very little effect of well pads on nesting success, while roads had a greater impact. Savannah sparrow and chestnut-collared longspur clutch sizes and fledgling numbers per nest were lower near gas well pads and cattle water sources, suggesting lower quality habitat in these areas. Large-sized predators occurred less in areas with older well pads. Concentrations of new well pads may have greater effects on chestnut-collared longspur reproductive success. Minimizing habitat disturbance surrounding gas well pads, and reducing abundance of roads, should minimize impacts on reproductive success for most grassland songbirds.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.327

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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