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Record W3014860656 · doi:10.1371/journal.pone.0230952

Using Maize δ15N values to assess soil fertility in fifteenth- and sixteenth-century ad Iroquoian agricultural fields

2020· article· en· W3014860656 on OpenAlexaboutno aff
John P. Hart, Robert S. Feranec

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsSubsistence agricultureArchaeologyAgricultureFifteenthEdaphicArchaeological evidenceGeographyAgroforestryBiologyHistoryEcologyAncient historySoil water

Abstract

fetched live from OpenAlex

Native Americans developed agronomic practices throughout the Western Hemisphere adapted to regional climate, edaphic conditions, and the extent of dependence on agriculture for subsistence. These included the mounding or "corn hill" system in northeastern North America. Iroquoian language speakers of present-day New York, USA, and Ontario and Québec, Canada were among those who used this system. While well-known, there has been little archaeological documentation of the system. As a result, there is scant archaeological evidence on how Iroquoian farmers maintained soil fertility in their often-extensive agricultural fields. Using δ15N values obtained on fifteenth- and sixteenth-century AD maize kernels from archaeological sites in New York and Ontario, adjusted to take into account changes that result from charring as determined through experiments, we demonstrate that Iroquoian farmers were successful at maintaining nitrogen in their agricultural fields. These results add to our archaeological knowledge of Iroquoian agronomic practices. Our results also indicate the potential value of obtaining δ15N values on archaeological maize in the investigation of Native American agronomic practices.

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 score0.001
Threshold uncertainty score0.448

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 studies0.0000.000
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 head0.094
GPT teacher head0.228
Teacher spread0.134 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicArchaeology and ancient environmental studiesFrench-language works237,207