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Record W1609796528 · doi:10.5751/es-02980-140214

From Risk Assessment to Knowledge Mapping: Science, Precaution, and Participation in Disease Ecology

2009· article· en· W1609796528 on OpenAlexvenueno aff
Andy Stirling, Ian Scoones

Bibliographic record

VenueEcology and Society · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicRisk Perception and Management
Canadian institutionsnot available
FundersWildlife Conservation SocietyEconomic and Social Research CouncilUnited States Agency for International Development
KeywordsEcologyDiseaseRisk assessmentApplied ecologyEnvironmental resource managementGeographyBiologyComputer scienceEnvironmental scienceBiodiversityMedicine

Abstract

fetched live from OpenAlex

Stirling, A. C., and I. Scoones. 2009. From risk assessment to knowledge mapping: science, precaution and participation in disease ecology. Ecology and Society 14(2): 14. https://doi.org/10.5751/ES-02980-140214

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)0.037
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.112
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0050.030
Scholarly communication0.0180.035
Open science0.0020.016
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0100.001

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 head0.376
Teacher spread0.354 · 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.

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

Citations97
Published2009
Admission routes1
Has abstractyes

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