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Record W6976651354 · doi:10.6068/dp172ce3321ac47

TREND: United States Census Bureau. International Trade Datasets: Imports by Standard International Trade Classification (SITC) Code | Indicator: Imports for Consumption, CIF Value | Code: 59331, 01/2013 - 02/2020. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-067-012

2020· other· en· W6976651354 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueData Planet · 2020
Typeother
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsnot available
Fundersnot available
KeywordsCensusCommodityValue (mathematics)Principal (computer security)Official statisticsInternational standardTrade barrier

Abstract

fetched live from OpenAlex

United States Census Bureau. International Trade Datasets: Imports by Standard International Trade Classification (SITC) Code | Indicator: Imports for Consumption, CIF Value | Code: 59331, 01/2013 - 02/2020. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 001-067-012 Dataset: Provides statistics on imports to the US based on the Standard International Trade Classification (SITC) commodity classification system defined by the United Nations. For more information on SITC, visit https://unstats.un.org/unsd/tradekb/Knowledgebase/50017/Standard-International-Trade-Classification-Revision-4 The Monthly and Annual International Trade Datasets provide detailed data on trade between the United States and its international trade partners. The ITD provide the most comprehensive current month and cumulative year-to-date export and import statistics using multiple commodity classification systems. Previously released trade data are revised annually with the publication of April statistics. Data on US exports of merchandise from the US to all countries, except Canada, are compiled from the Electronic Export Information (EEI) filed by the US Principal Party of Interest or their agents through the US Customs' Automated Commercial Environment (ACE). Filing the EEI is mandatory under Chapter 9, Title 13, United States Code. Qualified exporters, or their agents, submit EEI data by automated means directly to the US Census Bureau. Data on US imports of merchandise are compiled primarily from automated data submitted through the US Customs' Automated Commercial Environment (ACE). Other sources of import data include import entry summary forms, warehouse withdrawal forms, and Foreign Trade Zone documents. Data on imports of electricity and natural gas from Canada are obtained from Canadian sources. Statistics are available by district (or port) of exportation (for exports) or entry (for imports) and by trading partner. https://www.census.gov/data/developers/data-sets/international-trade.html Category: International Relations and Trade Subject: International Trade, Imports Source: United States Census Bureau The United States 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. https://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.

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)0.001
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.295
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