MétaCan
Menu
Back to cohort
Record W7005842923

Stronger Manufacturing Growth Expected in the Second Quarter

2019· article· en· W7005842923 on OpenAlexaboutno aff

Bibliographic record

VenueChapman University Digital Commons (Chapman University) · 2019
Typearticle
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PurchasingManufacturingChinaProductivityManufacturing sector
DOInot available

Abstract

fetched live from OpenAlex

ORANGE, CA -According to a survey of purchasing managers, the California manufacturing economy is expected to expand at a higher rate in the second quarter of 2019 compared to the first quarter."The California Composite Index, measuring overall manufacturing activity, increased from 61.2 in the first quarter to 63.3 in the second quarter, indicating a higher growth rate" said Dr. Raymond Sfeir, director of the purchasing managers' survey.This is happening at the same time that the national economy added 541,000 jobs in the first quarter of 2019.Production, inventories of purchased materials, new orders and employment are expected to grow at a higher rate compared to the first quarter.Commodity prices are expected to rise at a slower rate for the fourth consecutive quarter.Supplier deliveries are expected to slow at a slower rate.Respondents commented on the increase in wages and the high cost of living in California which are leading firms to shift either some of their operations or the whole manufacturing plant to other states.The trade dispute with China remains a critical issue to many purchasing managers.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.004

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 head0.020
GPT teacher head0.201
Teacher spread0.180 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueChapman University Digital Commons (Chapman University)Same topicBiological and pharmacological studies of plantsFrench-language works237,207