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Record W6901382672 · doi:10.6068/dp14ba7cd5a2b19

Trend 2005 - 2011. Statistics Canada. CANSIM: Business Performance and Ownership - Financial Statements and Performance | Country: Canada | Table: Sound recording and music publishing, summary statistics, by North American Industry Classification System (NAICS) | Variable: Music publishers, Operating expenses (x 1,000,000) | Units: , 2005-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-022.

2015· other· en· W6901382672 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueEconomic statisticsIncome statementDescriptive statisticsCensusBalance sheetYear-endingFinancial statementDebtNational accounts

Abstract

fetched live from OpenAlex

Statistics Canada (2015). CANSIM: Business Performance and Ownership - Financial Statements and Performance | Country: Canada | Table: Sound recording and music publishing, summary statistics, by North American Industry Classification System (NAICS) | Variable: Music publishers, Operating expenses (x 1,000,000) | Units: , 2005-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 075-001-022. Dataset: Provides financial data prepared by incorporated businesses in Canada on their financial position and performance, such as statistics on revenue or profit growth, profit margins, debt to equity, and return on equity. These data include items from the balance sheet, the income statement and the statement of changes in financial position, and information that describes an industry or a firm’s performance for a specific period using financial data. CANSIM is Statistics Canada's key socioeconomic database. The datasets included here provide statistics on the Canadian population, and the nation’s resources, economy, society, and culture. In addition to conducting a Census every five years, approximately 350 active surveys are conducted on virtually all aspects of Canadian life. Statistics are provided for the nation as a whole, provinces, and other subnational geographies where available. Category: Industry, Business, and Commerce Source: Statistics Canada Established as Canada's central statistical office by the Statistics Act of 1985, Statistics Canada is required to "collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and conditions of the people of Canada." Its main objectives are to provide statistical information and analysis about Canada’s economic and social structure and to promote sound statistical standards and practices. http://www.statcan.gc.ca/ Subject: Businesses, Financials

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)0.002
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.925
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.020
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.041
Science and technology studies0.0030.001
Scholarly communication0.0050.003
Open science0.0050.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0750.060

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 head0.246
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

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
Published2015
Admission routes1
Has abstractyes

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