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Record W7036885874

Courtland Street, Lake George : a bioarchaeological study of the skeletal foot morphology of early Revolutionary War soldiers

2021· article· en· W7036885874 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Archive - University at Albany (University at Albany, State University of New York) · 2021
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
Fundersnot available
KeywordsBattleFoot (prosody)George (robot)State (computer science)Spanish Civil War
DOInot available

Abstract

fetched live from OpenAlex

In 2019, an unmarked burial ground was discovered in the town of Lake George, NY. Under the leadership of the Bioarcheology department at the New York State Museum, numerous interments were excavated. A few of the remains had been bisected, leaving only their lower limbs. Additionally, many of the remains were commingled within a large mound of dirt. Upon analysis, the remains recovered from the Courtland Street site were determined to be associated with the Revolutionary War and the early Battle of Quebec in 1775. Due to the state of the remains, it was only possible to focus an analysis on one aspect of the skeleton. Therefore, the subject of this thesis was to investigate the foot morphology of this group as a whole and to see if, and how, soldier’s feet were affected by their involvement in the Revolutionary War. This thesis is separated into two parts; first, the feet of commingled remains were reconstructed. Once this was completed, investigation was completed on whether foot injuries, such as stress fractures, were present within this group. In addition, the musculoskeletal aspects of the metatarsals and non-metric traits, such as accessory facets of the tarsal bones, were studied.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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