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Record W2919945930 · doi:10.14351/0831-4985-32.1.1

Conservation of Subfossil Bones from a Lacustrine Setting: Uncontrolled and Controlled Drying of Late Quaternary Vertebrate Remains from Cold Lake, Western Canada

2018· article· en· W2919945930 on OpenAlexaffvenueabout
Christina I. Barrón-Ortiz, Matthew R. Sawchuk, Carmen Li, Christopher N. Jass

Bibliographic record

VenueCollection Forum · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsRoyal Alberta Museum
Fundersnot available
KeywordsSubfossilQuaternaryDelamination (geology)CrackingAntlerGeologyPaleontologyMaterials scienceComposite materialBiologyEcologyTectonics

Abstract

fetched live from OpenAlex

Abstract Water-saturated vertebrate remains (e.g., bone, antler, and ivory) are particularly challenging to stabilize for long-term storage, research, and analysis. These types of specimens are sensitive to damage caused by water loss, which frequently results in delamination, twisting, and cracking. The recovery of late Quaternary vertebrate remains from underwater areas of Cold Lake, western Canada, prompted us to conduct a series of analyses to better understand the preservation of the remains and their susceptibility to damage, and to test different conservation techniques to achieve successful drying. X-ray fluorescence analysis of a sample of specimens revealed that the remains have particularly high iron concentrations, a condition that might have contributed to weaken their structure, further compromising their integrity when drying. Additionally, we found that certain bone elements, such as long bones, are more susceptible to severe surface delamination than others, and as a result these specimens should be monitored more closely during their treatment. Of the four drying methods we tested, controlled air-drying produced the best results, followed by solvent-drying. In contrast, vacuum freeze-drying and vacuum freeze-drying with 20% v/v Acrysol WS-24 in water, an acrylic dispersion, while rapid, resulted in differing degrees of delamination and cracking.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.367

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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

Citations5
Published2018
Admission routes3
Has abstractyes

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Same venueCollection ForumSame topicPleistocene-Era Hominins and ArchaeologyFrench-language works237,207