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Record W2125941628 · doi:10.22230/jem.2015v15n2a576

Science-Based Guidelines for Managing Northern Goshawk Breeding Areas in Coastal British Columbia

2015· article· en· W2125941628 on OpenAlexafffundabout
Erica L. McClaren, Todd Mahon, Frank I. Doyle, William L. Harrower

Bibliographic record

VenueJournal of Ecosystems and Management · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsGovernment of British Columbia
FundersHabitat Conservation Trust FoundationMinistry of Forests, Lands and Natural Resource OperationsMinistry of EnvironmentParks Canada
KeywordsAccipiterHabitatGeographyForagingFisheryEcologyEnvironmental resource managementPredationBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Northern Goshawks (Accipiter gentilis laingi) have been recognized as a species of management concern in western North America for over 20 years. One of the most significant factors threatening Northern Goshawk populations in coastal British Columbia is the loss and fragmentation of structurally old and mature forests they use for breeding, foraging, and roosting. The goal of this report is to provide science-based guidelines for qualified environmental professonals to assist in their decision-making processes concerning Northern Goshawk habitat management in coastal British Columbia. These guidelines were previously unavailable or inconsistent and did not provide a thorough review of the scientific literature. The best management practices presented here are intended for use by qualified environmental professonals and managers when undertaking industrial activities, primarily forestry, around Northern Goshawk breeding areas within coastal British Columbia.

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)0.009
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.393
Threshold uncertainty score0.791

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0050.002
Scholarly communication0.0040.002
Open science0.0050.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.037
GPT teacher head0.257
Teacher spread0.220 · 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 designTheoretical or conceptual
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

Citations6
Published2015
Admission routes3
Has abstractyes

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