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Record W2611644646 · doi:10.2110/palo.2016.047

BONE LOSS FROM CARCASSES IN MEDITERRANEAN ECOSYSTEMS

2017· article· en· W2611644646 on OpenAlexfundno aff
Eloísa Bernáldez Sánchez, Esteban García‐Viñas, Inés Sánchez-Donoso, Jennifer A. Leonard

Bibliographic record

VenuePalaios · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsnot available
FundersInstitute of Aboriginal Peoples HealthJunta de Andalucía
KeywordsMediterranean climateEcosystemGeologyMediterranean areaEnvironmental sciencePhysical geographyGeographyEcologyBiology

Abstract

fetched live from OpenAlex

Abstract: In order to interpret fossil and sub-fossil associations of vertebrates, it is important to understand how carcasses degrade in nature. Here we describe the process of bone loss from of 32 carcasses from eight species of terrestrial mammals over two to 63 months in two Mediterranean ecosystems in the southwest of the Iberian Peninsula. The carcasses ranged in mass from 5 kg to over 450 kg. These data allow the quantitative description of the dynamics of degradation in three time phases defined by changes in the rate of bone loss as measured by the Skeletal Conservation Index (SCI). The SCI values estimated for each phase of degradation is considered the fossil potentiality of the carcass. In the first phase, very few bones were lost, followed by a phase of high bone loss driven by scavengers. The rate of bone loss reduced greatly again in the final phase, which was driven primarily by abiotic, environmental factors. The largest carcasses spend a longer time in each phase, and also had a higher SCI at the end of Phase II. The smallest carcasses experienced a much higher variance in degradation, had significantly lower SCI, and many of the smallest carcasses were consumed completely in a short period of time. Differences between localities were observed regarding SCI values. Presence or absence of tree coverage in the place where the carcass was located also had a significant effect on SCI. These data highlight the importance of considering the contemporaneous scavengers when interpreting animals from paleontological contexts. These data also explain the bias observed in many ancient sites whereby larger animals are over represented.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.324
Teacher spread0.280 · 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.

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

Citations7
Published2017
Admission routes1
Has abstractyes

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