MétaCan
Menu
Back to cohort
Record W1591210873

A Fresh Look at the Taxonomy of Midcontinental Sandhill Cranes

2005· article· en· W1591210873 on OpenAlexfundaboutno aff
Douglas H. Johnson, Jane E. Austin, Jill A. Shaffer

Bibliographic record

VenueLincoln (University of Nebraska) · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersU.S. Geological SurveyU.S. Fish and Wildlife ServiceOklahoma Department of Wildlife ConservationMinistry of Natural ResourcesYale UniversityMinnesota Department of Natural Resources
KeywordsSubspeciesSandhillGrus (genus)PopulationGeographyRecreationEcologyBiologyHabitatDemography
DOInot available

Abstract

fetched live from OpenAlex

The midcontinental population of sandhill crane (Grus canadensis) includes about 500,000 birds and provides valuable recreational crane-watching and hunting opportunities in Canada and the United States. It comprises three subspecies, one of which (G. c. rowani) was of uncertain taxonomic status and another of which (G. c. tabida) merited protection from excessive harvest due to its small population size. We obtained measurements of cranes used by Johnson and Stewart (1973) and additional crane specimens to 1) evaluate the subspecies designation of midcontinental sandhill cranes and 2) to seek improved methods for classifying cranes from selected measurements. We found that the three named subspecies are in fact morphologically distinct, although there is a general gradient of smaller birds breeding in the far north to larger birds breeding at more southerly latitudes. We were not able to find better ways of identifying subspecies; in particular we could not find a reliable method that did not require knowledge of the sex of an individual crane.

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 score0.166
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.178
Teacher spread0.168 · 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

Citations11
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueLincoln (University of Nebraska)Same topicAvian ecology and behaviorFrench-language works237,207