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Peering Through The Sands Of Time: A Geophysical Investigation Of Two Buried Ships

2003· article· en· W2324065228 on OpenAlexaboutno aff
R. James Mickle, Anthony L. Endres, Jim McLay, Kenneth A. Cassavoy

Bibliographic record

Venue16th EEGS Symposium on the Application of Geophysics to Engineering and Environmental Problems · 2003
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsGround-penetrating radarExcavationContext (archaeology)GeologyArchaeologyRadarGeotechnical engineeringPaleontologyEngineeringHistoryTelecommunications

Abstract

fetched live from OpenAlex

In the Spring of 2001, the wooden ribs of an unknown ship were discovered protruding from the<br>beach in Southampton, Ontario. A ground penetrating radar (GPR) survey was performed over the<br>wreck as part of the site characterization. Near surface scattering was used to infer zones of buried<br>wreckage. Test pits were dug based on locations of GPR anomalies and the remains of a sizeable ship<br>and a small barge were partially unearthed. A subsequent magnetic survey was performed to delineate<br>ferrous structural artifacts.<br>The comparison of the geophysical data and excavation results demonstrates the ability of each<br>method to detect and delineate buried structures. Direct interpretation of the GPR profile data highlights<br>the general area of known wreckage, but an exact delineation is not possible. In the case of the magnetic<br>survey, major structural features of the vessels are clearly identifiable and yield information on the size<br>and orientation of each vessel.<br>In October, 2002, a third excavation took place to investigate details of the larger ship. During<br>the course of this excavation, a small deck cannon was discovered among the remains, coincident with a<br>large reverberation event on one of the GPR profiles. This discovery has important historical<br>implications and is considered an extremely significant find in the archaeological context of the Great<br>Lakes.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.371

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 head0.009
GPT teacher head0.175
Teacher spread0.166 · 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 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

Citations0
Published2003
Admission routes1
Has abstractyes

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