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Record W6931717998 · doi:10.5683/sp3/fwuum3

Postal Code Conversion File [Canada], March 2006, Census of Canada 2001

2006· dataset· en· W6931717998 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2006
Typedataset
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
Fundersnot available
KeywordsCensusData fileGeographic information systemGeocodingCode (set theory)Location

Abstract

fetched live from OpenAlex

The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. In April 1983, the Geography Division released the first version of the Postal Code Conversion File, which linked postal codes to census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect postal code changes provided by Canada Post Corporation. Every five years, the postal code linkages on the Postal Code Conversion File are “converted” to the latest census geographic areas. The original Postal Code Conversion File was linked to the 1981 Census geographic areas. Since then, the Postal Code Conversion File has undergone four “conversions”, following the 1986, 1991, 1996 and 2001 censuses. A revised automated system was used for the 1996-2001 conversion. The 2001 Census postal codes reported by respondents were used to validate the Postal Code Conversion File links. Restricted File Access will be granted only to DLI and Odesi Subscribing Institutions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.196
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.029
Science and technology studies0.0040.001
Scholarly communication0.0040.002
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1960.078

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 head0.023
GPT teacher head0.295
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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
Published2006
Admission routes1
Has abstractyes

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