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Record W6969544105 · doi:10.5284/1127323

Historic Building Recording A14 Cambridge To Huntingdon Improvement Scheme: Milestones On The A1 And A14, Alconbury To Cambridge Cambridgeshire

2018· article· en· W6969544105 on OpenAlexaboutno aff

Bibliographic record

VenueArchaeology Data Service · 2018
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsLetteringExtant taxonPeriod (music)Late 19th centuryMileHistorical record

Abstract

fetched live from OpenAlex

The recording was carried out in line with Historic England Level 2 historic building recording guidelines. The objective of Historic England (HE) Level 2 building recording is to provide a descriptive record of an extant structure in accordance with the Historic England document Understanding Historic Buildings: A guide to good recording practice (HE 2016). It provides a systematic account of a building or structure's origins, development and use. Six milestones/markers were recorded during the survey, distributed over a distance of approximately 24.5 km: two (milestones 213 and 552) along the route of the A1 dual carriageway between Alconbury and Buckden, northwest of Brampton, Cambridgeshire. The post-medieval period saw a marked increase in trade, particularly towards the capital and was accompanied by an improvement and widening of main trading routes. Mile markers adhering to a standardised unit of measurement allowed for accurate pricing and scheduling of journeys. The earliest such markers were likely carved from timber posts but were rapidly superseded by stone carved pillars of local stone, into which the lettering was carved and picked out with paint. Such markers were susceptible to weathering and erosion and the painted letters required renewal. The 19th century saw the replacement of many such markers with cast iron ones which were mould produced.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0070.013
Research integrity0.0000.001
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 head0.043
GPT teacher head0.282
Teacher spread0.239 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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