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Surveying

2017· other· en· W4244330938 on OpenAlexaff
Andrew Hunter

Bibliographic record

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicArchaeological Research and Protection
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeomaticsMesopotamiaGeographyVariety (cybernetics)Work (physics)SurveyorDisseminationCartographyNatural (archaeology)Remote sensingNatural resourceArchaeologyEnvironmental planningEngineeringComputer sciencePolitical scienceArtificial intelligence

Abstract

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Surveying has a very long history, with evidence of surveyors' work dating back to the Egyptian pharaohs and the construction of the pyramids, and to landownership systems in early Mesopotamia (the region covered by the Tigris–Euphrates river system). Today, surveying, also referred to as geomatics, continues to develop the science and technology used to determine the location of natural and man‐made features on the surface of the earth. New survey technologies have made it possible to map large tracts of land quickly and accurately, and to process and disseminate the data in a variety of formats to clients and individuals/groups interested in the planning and administration of land and sea, and the resources that they contain.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.680
Threshold uncertainty score0.985

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.000

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 head0.267
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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