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Record W6920305136 · doi:10.6068/dp1508775301830

Ranking of Counties (2011). United States Census Bureau. County Business Patterns by NAICS Code (2003-Current): Annual Payroll | Country: USA | State: North Carolina | NAICS_ID: 0 | NAICS Code*: Total, 2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 001-007-003.

2015· other· en· W6920305136 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPayrollCensusRevenueRanking (information retrieval)Production (economics)Government (linguistics)Agency (philosophy)Social securityQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Conquest Statistical Datasets. (2014). County Business Patterns by NAICS Code (2003-Current): Annual Payroll, 2003 - 2011 [Data file]. Retrieved from http://www.data-planet.com Dataset: Shows annual business payroll, by State, county, and NAICS industry. Total annual payroll includes all forms of compensation, such as salaries, wages, commissions, bonuses, vacation allowances, sick-leave pay, and the value of payments inkind (e.g., free meals and lodgings) paid during the year to all employees. Data are from the United States Census Bureau's County Business Patterns (CBP), an annual series that provides national and subnational data on the distribution of economic data by size and industry. CBP covers most of the country's economic activity. CBP basic data items are extracted from the Business Register, a file of all known single and multi-establishment employer companies maintained and updated by the Census Bureau. The annual Company Organization Survey provides individual establishment data for multi-establishment companies. Data for single-establishment companies are obtained from various Census Bureau programs, such as the Annual Survey of Manufactures and Current Business Surveys, as well as from administrative records of the Internal Revenue Service, the Social Security Administration, and the Bureau of Labor Statistics. The series excludes data on self-employed individuals, employees of private households, railroad employees, agricultural production employees, and most government employees. CBP covers most NAICS industries, excluding crop and animal production (NAICS 111,112); rail transportation (NAICS 482); Postal Service (NAICS 491); pension, health, welfare, and vacation funds (NAICS 525110, 525120, 525190); trusts, estates, and agency accounts (NAICS 525920); private households (NAICS 814); and public administration (NAICS 92). Category: Industry, Business, and Commerce, Labor and Employment Source: United States Census Bureau Subject: Businesses, Compensation, Salaries, Payroll, Wages, Employer Costs

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.546
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0080.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.012

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 head0.040
GPT teacher head0.292
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

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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