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Record W2524301348 · doi:10.1080/00934690.2016.1234897

A human-centered GIS approach to modeling mobility on southern Baffin Island, Nunavut, Canada

2016· article· en· W2524301348 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Field Archaeology · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of ManitobaUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsWatershedGeographyArchaeologyResource (disambiguation)Elevation (ballistics)Land coverLand useEcologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Southern Baffin Island has been occupied for several millennia, but its enormous size, coupled with scarcity of identified inland archaeological sites that can be confidently linked to coastal occupations, makes modeling ancient seasonal mobility across the region through traditional cost-surface least-cost pathway approaches impractical. We present a method that combines weighted multi-criteria cost surface analysis with a watershed function to create a “mobility-shed” of non-winter travel pathways covering the study area. We evaluate the predictive utility of the resulting pathways for future archaeological survey by assessing their spatial relationships to known archaeological sites. The results of this comparison suggest that elevation and land cover criteria should be augmented with ethnographic and resource availability data to model mobility in this region.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.811

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.053
GPT teacher head0.336
Teacher spread0.283 · 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