MétaCan
Menu
Back to cohort
Record W1892771595 · doi:10.51347/jum.v9i1.3914

Mapping and analysing medieval built form using GPS and GIS

2004· article· en· W1892771595 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUrban Morphology · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGlobal Positioning SystemPlan (archaeology)Geographic information systemGeographyGIS applicationsComputer scienceCartographyArchaeology

Abstract

fetched live from OpenAlex

Drawing upon recent research experiences of using a Global Positioning System (GPS) and Geographical Information Systems (GIS), this paper sets out how spatial technologies can be used in the study of medieval built form. The paper focuses particularly on the use of differential GPS and ArcGIS in mapping and analysing the plan of Winchelsea, an English medieval 'new town' established in the 1280s. The approach used to conduct this research is outlined here, with comments on the practicalities of using GPS and GIS in historical urban morphology. Although the research on which this paper is based is at a preliminary stage, the paper offers a working method for those interested in using spatial technologies to build upon existing methods of morphological study, namely town-plan analysis and metrological analysis. Some preliminary research findings relating to the planning of medieval Winchelsea are also presented.

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.

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)0.001
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 score0.116
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.040
GPT teacher head0.297
Teacher spread0.257 · 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