MétaCan
Menu
Back to cohort
Record W2111082879

What is an address in South Africa

2007· article· en· W2111082879 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

VenueUpSpace Institutional Repository (University of Pretoria) · 2007
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsCanadian Society of Intestinal Research
Fundersnot available
KeywordsStandardizationVariety (cybernetics)Set (abstract data type)Political scienceStandardized testComputer scienceLawPsychology
DOInot available

Abstract

fetched live from OpenAlex

Addresses come in many forms as they have a variety of uses. In our paper we illustrate the need for standardized addresses in South Africa by describing scenarios where standardized addresses are required, or where standardized addresses would improve the current situation. We present the eleven address types described in the current draft South African address standard (SANS 1883), which has been developed under the auspices of the South African Bureau of Standards. We go on to show that these address types represent an all-encompassing description of an address in South Africa. The address types have to accommodate the current situation where there are no mandated authorities that assign standardized addresses according to a set of guidelines, and we provide a critical evaluation of this situation. Our contribution is threefold: illustrating the need for standardized addresses, showing that there is an all-encompassing description for an address in South Africa, and describing the potential negative impact of the current lack of mandated authorities on unambiguous address specification and the benefits that address standardization would bring.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.723

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 studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.000
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 head0.035
GPT teacher head0.236
Teacher spread0.202 · 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