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Record W3146769229 · doi:10.1021/cen-09611-buscon4

Chemical industry slams Trump steel tariffs

2018· article· en· W3146769229 on OpenAlex
Alex Tullo

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

VenueC&EN Global Enterprise · 2018
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

The Trump administration’s decision to impose tariffs on imported steel and aluminum is unpopular with many industries, including the chemical sector. The U.S. industry’s leading trade group, the American Chemistry Council (ACC), is condemning the measure, saying it will hurt industry competitiveness. In a White House ceremony before steel and aluminum industry workers on March 8, President Donald J. Trump signed a proclamation imposing a 25% tariff on imported steel and a 10% duty on aluminum. Trump left the door open to trading partners Canada and Mexico, as well as military allies, being exempt from the measures. “Steel is steel,” Trump said. “If you don’t have steel, you don’t have a country.” The administration has grown increasingly concerned about steel. Last month, the Commerce Department issued a report calling for the U.S. to reduce steel imports. Imports grew at double-digit rates in 2017, the report noted, and the U.S. now

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.338
Teacher spread0.321 · 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