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Record W3084287341 · doi:10.1016/j.fsisyn.2020.09.001

Perspectives on the establishment of a canadian human taphonomic facility: The experience of REST[ES]

2020· article· en· W3084287341 on OpenAlexafffundabout
Emily Pecsi, Gilles Bronchti, Frank Crispino, Shari L. Forbes

Bibliographic record

VenueForensic Science International Synergy · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsRest (music)TaphonomyEnvironmental resource managementPolitical scienceBusinessOperations managementEngineeringGeographyEnvironmental scienceArchaeologyMedicine

Abstract

fetched live from OpenAlex

REST[ES] is the first Canadian human taphonomic facility (HTF) dedicated to research and training relating to human decomposition in a northern temperate climate. The following paper outlines the measures taken to successfully establish, open and operate this novel Canadian HTF with particular focus on: project team and partnerships, facility location, approvals and permits, infrastructure and social acceptability. It is intended that our experience of establishing REST[ES] may serve as an example to help others with the establishment of future HTFs, thus contributing to the expansion in the global accessibility to human decomposition research and training.

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)0.011
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0390.014
Scholarly communication0.0070.003
Open science0.0030.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.035
GPT teacher head0.248
Teacher spread0.213 · 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

Citations26
Published2020
Admission routes3
Has abstractyes

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