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Record W2533008654

Preparation of regional shorebird monitoring plans

2005· article· en· W2533008654 on OpenAlexaboutno aff
Jonathan Bart, Ann E. Ellison Manning, Susan M. Thomas, Catherine S. Wightman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyBorealPopulationTemperate climateEcologyBiologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Shorebird monitoring programs in Canada and the United States are being developed under the auspices of PRISM, the Program for Regional and International Shorebird Monitoring. PRISM provides a single blueprint for implementing the monitoring proposals in the shorebird conservation plans prepared recently in Canada and the United States. It includes four segments: arctic and boreal breeding surveys, temperate breeding surveys, temperate nonbreeding surveys, and neotropical surveys. A separate document, available at http://amap.wr.usgs.gov, provides an overview of PRISM. Temperate non-breeding surveys have the potential to contribute to four of the five goals of PRISM: monitor stopover sites during the spring and fall migration, elucidate habitat relationships, help local managers meet shorebird conservation goals, and measure population trends. This program seeks to standardize site selection, data collection, and data storage among existing initiatives including the International Shorebird Survey, Maritimes Shorebird Survey, and Western Shorebird Survey. The temperate non-breeding surveys involve a major effort to identify shorebird concentration sites and develop ways to survey them for shorebirds. These analyses are termed “regional assessments” and are being conducted throughout southern Canada and the United States. This document provides guidelines for preparing regional assessments. It is intended for people who will use the shorebird survey data, so they can understand the sampling plans used to select sites, and for other waterbird specialists who may be interested in adapting the approach for their species. More detailed procedures and examples are available at http://amap.wr.usgs.gov.

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)0.006
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.157
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.005
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0590.017

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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2005
Admission routes1
Has abstractyes

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