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Record W2911662697 · doi:10.1016/j.jasrep.2019.01.012

Production origins and matrix constituents of spiculate pottery in Florida, USA: Defining ubiquitous St Johns ware by LA-ICP-MS and XRD

2019· article· en· W2911662697 on OpenAlexaboutno aff
Lindsay Bloch, Neill J. Wallis, George D. Kamenov, J. M. Jaeger

Bibliographic record

VenueJournal of Archaeological Science Reports · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPotteryMuckArchaeologySponge spiculeWoodlandWetlandGeologyGeographySoil sciencePaleontologyEcologyBiology

Abstract

fetched live from OpenAlex

Fine-grained “chalky” pottery containing microscopic sponge spicules is commonly recovered from archaeological sites throughout peninsular Florida, but many questions remain about its composition and origins. It is identified by different names, but most are associated with the St. Johns Type series. While it has been commonly assumed to originate in the St. Johns River drainage for which it is named, the prevalence of pottery with these characteristics in other locations has presented the likelihood of independent production in multiple places. In this study, we conducted LA-ICP-MS and XRD analysis of spiculate pottery from three Woodland period (ca. 1000 BCE to 1000 CE) sites, along with comparative clay samples, in order to characterize the raw materials and determine the geographic scope of production. Our results support the theory that this ware was independently produced across peninsular Florida. We further evaluate the hypothesis that this pottery was made with common wetland muck, through consideration of the material properties of muck constituents. This project emphasizes the importance of an ecosystem framework for understanding the long history of spiculate pottery production and its geographic spread within Florida.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.254
Teacher spread0.238 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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