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Record W2523470272 · doi:10.1021/cen-v081n015.p018

STOCKS FALL IN FIRST QUARTER

2003· article· en· W2523470272 on OpenAlex
WILLIAM J. STORC, ANN THAYER

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

VenueChemical & Engineering News · 2003
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsnot available
Fundersnot available
KeywordsCitationQuarter (Canadian coin)Social mediaIconLibrary scienceComputer scienceWorld Wide WebHistory

Abstract

fetched live from OpenAlex

FIRST THERE WAS THE SPECTACULAR rise in oil and, especially, natural gas prices; then concerns about consumer confidence; then came the war in Iraq. All caused uncertainty on Wall Street, and the stock market hardly had a chance. Consequently, neither did chemical, pharmaceutical, and biotechnology stocks. Each of these market sectors was affected by one or more of the concerns swirling around Wall Street. Chemical companies had the misfortune to be hit by all these events, plus a few more. The result: C&EN's chemical company stock index fell 10.3% from the end of the fourth quarter of 2002 to the end of the first quarter of 2003, closing at an inauspicious 125 (1992 = 100). During the quarter, as the U.S. ramped up for the war in Iraq, the index hit a low of 115, the lowest the measure of stock performance has been since the second quarter of 1994. The decline in the chemical ...

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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