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Record W6969677930 · doi:10.5683/sp3/js0khf

International Travel Survey, 2006: Canadian Resident Trips Overseas File

2007· dataset· en· W6969677930 on OpenAlexaffabout

Bibliographic record

VenueBorealis · 2007
Typedataset
Languageen
FieldMaterials Science
TopicEnzyme Structure and Function
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsTRIPS architectureTourismCommissionPaymentPrivate sectorBusiness travel

Abstract

fetched live from OpenAlex

The International Travel Survey (ITS) is an ongoing survey conducted by Statistics Canada since the 1920s to meet the requirements of the Canadian System of National Accounts (Balance of Payments (BOP)). Through the years, the need for detailed characteristics of travellers for market research and industry planning was gradually incorporated in the survey. Today, the ITS provides a full range of statistics on the volume of international travellers and detailed characteristics of their trips such as expenditures, activities, places visited and length of stay. The ITS covers both Canadian residents returning from trips outside Canada and international visitors to Canada. In addition to fulfilling BOP requirements, the ITS is also being used by the Tourism Satellite Account (TSA), Customs Canada, the Canadian tourism Commission (CTC), provincial tourism agencies, the United States Department of Commerce and a number of private sector industries. The ITS is also used for reporting to international organizations such as the World Tourism Organization (WTO), the Organization for Economic Co-operation and Development and the Pacific-Asia Tourism Association.

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)0.004
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 score0.102
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.021
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.026

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 head0.021
GPT teacher head0.263
Teacher spread0.242 · 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
Published2007
Admission routes2
Has abstractyes

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