MétaCan
Menu
← Back to cohort
Record W7098872609

By Duanjie Chen The cheerful opening message in Finance Minister Jim Flaherty’s October 30

2007· article· en· W7098872609 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsIncome taxStatutory lawGovernment (linguistics)Tax reformCapital (architecture)Corporate taxNeutralityTax rate
DOInot available

Abstract

fetched live from OpenAlex

Economic Statement was that “Canada’s economic and fiscal fundamentals are rock solid. ” To promote capital investment, Flaherty announced a reduction in the general federal corporate income tax rate to 15 percent by 2012 from its current rate of 22.1 percent, and indicated he would seek the collaboration of the provinces and territories to reach a 25 percent combined federal-provincial-territorial statutory corporate income tax rate. The Finance Minister’s stated aim is to reduce Canada’s statutory corporate income tax rate relative to other G-7 countries; yet, while lower tax rates are welcome, comprehensive tax reforms remain very much needed. The most critical of these, in business taxation, is broadening the corporate income tax base to improve tax neutrality and enable future rate reductions, particularly at the provincial level. It would be regrettable if the federal government regarded the current proposed tax relief as “mission accomplished ” while leaving key reform opportunities unpursued. In evaluating current government plans for business taxation, it is

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: Other · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0420.014

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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
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
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicHIV/AIDS drug development and treatment→French-language works237,207→