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Record W2007189917 · doi:10.1038/npre.2009.3684.1

Results of a Wildlife Toxicology Workshop held by Smithsonian Institution: Identification & Prioritization of Problem Statements

2009· preprint· en· W2007189917 on OpenAlexaboutno aff
K. Christiana Grim, Mark D. Jankowski, Alonso Aguirre, Val R. Beasley, Anne Fairbrother, Sarah Gerould, Barnett A. Rattner, Teri Rowles, S. L. Monfort, Shirlee Tan

Bibliographic record

VenueNature Precedings · 2009
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifePopulationGovernment (linguistics)Action (physics)Environmental planningPrioritizationGeographyEngineeringEnvironmental healthManagement scienceMedicineEcologyBiology

Abstract

fetched live from OpenAlex

Abstract Background/Question/Methods On March 13-15, 2007 nearly 50 scientists and administrators from the US and Canada participated in a Smithsonian-sponsored Wildlife Toxicology Workshop. Invitees were from academic, government, conservation and private organizations and were selected to represent the diverse disciplines that encompass wildlife toxicology. The workshop addressed scientific and policy issues, strengths and weaknesses of current research strategies, interdisciplinary and science-based approaches in the study of complex contaminant issues, mechanisms for disseminating data to policy-makers, and the development of a partner network to meet the challenges facing wildlife toxicology over the next decade. Prior to the meeting, participants were asked to submit issues deemed to be of highest concern which shaped four thematic groups for discussion: Wildlife Toxicology in Education, Risk Assessment, Multiple Stressors/Complex Mixtures, and Sub-Lethal and Population-Level Effects. Results/Conclusions From these discussion groups, 18 problem statements were developed and prioritized outlining the most important issues to address now and into the future. Along with each problem statement participants developed potential solutions and action steps geared to move each issue forward. The workshop served as a stepping-stone for action in the field of wildlife toxicology. These problem statements and the resulting action items are presented to the inter-disciplinary wildlife toxicology community for adoption, and future work and action items in these areas are encouraged. For example, it was found that ecologists would be essential in addressing the implications of sublethal or lethal effects of contaminants on wildlife at the population, community and ecosystem scales. The workshop outcome looks to generate conversation and collaboration that will lead to the development of innovative research, future mechanisms for funding, workshops, working groups, and listserves within the wildlife toxicology community.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.001
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 head0.022
GPT teacher head0.321
Teacher spread0.298 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2009
Admission routes1
Has abstractyes

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