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Record W2485367834 · doi:10.1017/s0033822200041242

Radiocarbon Dating of Total Soil Organic Matter and Humin Fraction and Its Comparison with <sup>14</sup>C Ages of Fossil Charcoal

2001· article· en· W2485367834 on OpenAlexaff
Luiz Carlos Ruiz Pessenda, S. E. M. Gouveia, Ramón Aravena

Bibliographic record

VenueRadiocarbon · 2001
Typearticle
Languageen
FieldArts and Humanities
TopicAmazonian Archaeology and Ethnohistory
Canadian institutionsUniversity of Waterloo
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsHuminCharcoalRadiocarbon datingFraction (chemistry)Total organic carbonGeologyOrganic matterSoil waterEnvironmental scienceCarbon fibersMineralogyEnvironmental chemistrySoil organic matterSoil sciencePaleontologyChemistryMathematicsOrganic chemistry

Abstract

fetched live from OpenAlex

During the last decade radiocarbon dating has been used extensively in distinct regions of Brazil to provide information about soil chronology in paleoenvironmental studies. This paper presents 14 C data of soil organic matter (SOM), humin fraction, and charcoal in several soil profiles under natural vegetation from different Brazil locations (north, central, and southeast regions). The main objective is to compare the obtained 14 C dating of total SOM with humin, the oldest fraction of SOM. In order to validate the humin ages these data are compared with the age of charcoal collected at similar depths. The 14 C ages obtained on charcoal were, in most of the cases, in agreement with the humin fraction considering the experimental errors, or 20% older in average. The dates obtained from total SOM showed significantly younger ages than the humin fraction indicating contamination by younger carbon. These results show the humin fraction is considered a reliable material for 14 C dating in soils. However, the humin fraction ages could be assumed as the minimum ages for carbon in soils.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.220
Teacher spread0.203 · 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 designBench or experimental
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

Citations222
Published2001
Admission routes1
Has abstractyes

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