MétaCan
Menu
Back to cohort
Record W6976653070 · doi:10.6068/dp1617137ecdb7

TREND: United States Census Bureau. Federal Aid and Assistance [Archive]: Total Funds | State: Alabama | Recipient*: All Recipients | Federal Program Name: WILDLIFE RESTORATION, 1997 - 2010. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-039-003

2018· other· en· W6976653070 on OpenAlexaboutno aff

Bibliographic record

VenueData Planet · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCensusGovernment (linguistics)Federal fundsPopulationAmerican Community SurveyState (computer science)PaymentStatutory lawQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

United States Census Bureau. Federal Aid and Assistance [Archive]: Total Funds | State: Alabama | Recipient*: All Recipients | Federal Program Name: WILDLIFE RESTORATION, 1997 - 2010. Data-Planet™ Statistical Datasets by Conquest Systems, Inc. Dataset-ID: 001-039-003 Dataset: Total funding from Federal and non-Federal sources for 600 Federal programs, as identified by the Catalog of Federal Domestic Assistance (CDFA). The Census Bureau's Financial Assistance Awards Data System (FAADS) contains data on financial assistance awards under approximately 600 federal programs, as identified by the Catalog of Federal Domestic Assistance (CDFA) While primarily concerned with assistance to state and local governments, all major programs providing transfer payments to individuals, discretionary project grants, loans, or insurance are covered. FAADS was created to meet statutory requirements for program-level review by state and local governments and by the Congress. Data from FAADS is included along with other data in the Consolidated Federal Funds Report (CFFR), which is also prepared by Census Bureau. https://www.census.gov/govs/www/faads.html Category: Government and Politics Subject: State Government, Local Government, Government Spending, Social Insurance Systems Source: United States Census Bureau The US Census Bureau is a bureau of the US Department of Commerce. The major functions of the Census Bureau are authorized by Article 2, Section 2 of the United States Constitution, which provides that a census of population shall be taken every 10 years, and by Title 13 and Title 26 of the United States Code of Federal Regulations. The Census Bureau is responsible for numerous statistical programs, including census and surveys of households, governments, manufacturing and industries, and for US foreign trade statistics. The first US census was conducted in 1790 for the purposes of apportioning state representation in the US House of Representatives and for the apportionment of taxes. http://www.census.gov

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), 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 score0.220
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0050.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.009

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 head0.034
GPT teacher head0.307
Teacher spread0.273 · 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueData PlanetFrench-language works237,207