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Record W7098495002

DECENNIAL STATISTICAL STUDIES DIVISIONInvestigation of Data Release Rules for Medians and Zero Estimates for the American Community Survey

2011· article· en· W7098495002 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies in Science
Canadian institutionsnot available
Fundersnot available
KeywordsMedianZero (linguistics)Statistical analysisJoint (building)Statistical hypothesis testingStatistical model
DOInot available

Abstract

fetched live from OpenAlex

for the ACS The paper attached summarizes results of an ACS Research and Evaluation project with ID # 00780 concerning new filtering methods for medians and zero estimates. These results were presented at the 2010 Joint Statistical Meetings in Vancouver, BC Canada. The attached paper was submitted for publication in the proceedings. If you have questions regarding it, please contact Karen King at (301) 763-1974 or Michael Starsinic at (301) 763-3606.

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)0.139
metaresearch head score (Gemma)0.270
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.139
Threshold uncertainty score0.734

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1390.270
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.011
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0460.028

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 head0.480
GPT teacher head0.395
Teacher spread0.086 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2011
Admission routes1
Has abstractyes

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