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Record W2012009008 · doi:10.1002/ps.439

Quantification of plasma and egg 4,4′‐dinitrocarbanilide (DNC) residues for the efficient development of a nicarbazin‐based contraceptive for pest waterfowl

2002· article· en· W2012009008 on OpenAlexaboutno aff
John J. Johnston, WALTER M. BRITTON, Alexander MacDonald, Thomas M. Primus, Margaret J Goodal, Christi A. Yoder, Lowell A. Miller, Kathleen A. Fagerstone

Bibliographic record

VenuePest Management Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
FundersNational Wildlife Research Center
KeywordsWaterfowlBrantaBiologyPEST analysisAnimal scienceEcologyHabitatGoose

Abstract

fetched live from OpenAlex

Urbanization and associated landscaping has increased the abundance of year-round habitat for waterfowl, resulting in vegetation damage, loss of recreational activities, air transportation mishaps and health hazards. As part of a research program to develop socially acceptable techniques for management of pest bird populations, we are evaluating nicarbazin as a contraceptive in pest and surrogate avian species. As reproductive studies with Canada Geese (Branta canadensis) are tedious due to the difficulty of conducting controlled field studies and/or breeding geese in captivity, we evaluated the effects of oral nicarbazin administration on the production and hatchability of chicken eggs. Blood plasma and egg DNC concentrations were correlated to contraceptive efficacy. Subsequent studies are being conducted with geese to determine the diet nicarbazin concentration required to produce the desired blood and plasma DNC concentrations. This approach permits the expeditious evaluation of formulations and dosing regimes by simply monitoring blood DNC concentrations in target species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.050
GPT teacher head0.253
Teacher spread0.203 · 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 designBench or experimental
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

Citations23
Published2002
Admission routes1
Has abstractyes

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