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Record W7161970425 · doi:10.82308/9929

Habitat use by a forest-dwelling bat community in the northern Great Lakes region

2000· dissertation· en· W7161970425 on OpenAlexaboutno aff
Thomas S. Jung

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSnagMyotis lucifugusUnderstoryHabitatTaigaWildlifeForagingCanopyOdocoileusVegetation (pathology)

Abstract

fetched live from OpenAlex

To examine bat - habitat relationships, ultrasonic detectors were used to sample bat activity among: old-growth white pine (Pinus strobus ), mature white pine, boreal mixedwood, and selectively-cut white pine stands in central Ontario. Within the stands, bats were sampled in the canopy, the understory layer, and within canopy gaps. Forest structure was measured within each of the stands. The activity of bats was compared among forest stand types, within the stands, and in relation to forest structure. Also, maintaining forest wildlife populations requires data on the use of snags (i.e. dead trees). To provide further resolution of the habitat requirements of forest-dwelling bats, radio telemetry and exit counts were used to investigate the roosting ecology of mouse-eared bats (Myotis lucifugus and M. septentrionalis). Characteristics of snags used by mouse-eared bats were compared with randomly located snags and random geographic points, at three spatial scales (focal tree, surrounding forest, and landscape). (Abstract shortened by UMI.)

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 score0.557
Threshold uncertainty score0.891

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.038
GPT teacher head0.233
Teacher spread0.195 · 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
Published2000
Admission routes1
Has abstractyes

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