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Record W161856566

Preliminary habitat suitability analysis for moose in mainland Nova Scotia, Canada.

2002· article· en· W161856566 on OpenAlexvenueaboutno aff
Tamaini Snaith, Karen Beazley, Frances MacKinnon, Peter N. Duinker

Bibliographic record

VenueAlces · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsHabitatGeographyEcologyPopulationWildlife conservationWildlife managementNova scotiaEnvironmental scienceBiology
DOInot available

Abstract

fetched live from OpenAlex

Ecosystem management for biological conservation should include consideration of landscape-scale processes such as the habitat requirements of focal species. Moose (Alces alces americana) have been identified as an appropriate target for focal attention in mainland Nova Scotia. Currently, the population is at risk, and strategies for conservation should include the protection of sufficient habitat to meet the spatial requirements of the population. Delineation of spatial habitat requirements calls for an understanding of species-habitat associations and the distribution of suitable habitat across the landscape. To this end, habitat suitability in Nova Scotia was assessed relative to four criteria: (1) food availability; (2) conifer cover; (3) mixed-wood cover; and, (4) aquatic resources. Model predictions were tested by comparing habitat suitability values to provincial pellet inventory data. Road density was found to be more important than habitat composition in determining moose pellet distribution. ALCES VOL. 38: 73-88 (2002)

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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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

Citations15
Published2002
Admission routes2
Has abstractyes

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