U.S. economy grew at a brisk 4.1 percent rate last quarter
Bibliographic record
Abstract
The U.S. economy accelerated last quarter at an annual rate of 4.1 percent, the government estimated Friday, as consumers spent tax-cut money, businesses stepped up investment and exporters rushed to ship their goods ahead of retaliatory tariffs. The U.S. economy surged in the April-June quarter, growing at an annual rate of 4.1 percent. That's the fastest pace since 2014......it's being driven by consumers who began spending their tax cuts and exporters who sought to get their products delivered ahead of retaliatory tariffs.The Commerce Department reports that the gross domestic product, the country's total output of goods and services, posted its best showing since a 4.9 percent gain in the third quarter of 2014.President Trump predicts growth will accelerate under his economic policies. But private forecasters cautioned that the April-June pace is unsustainable because it stems from temporary factors. The rest of the year is likely to see good, but slower growth of around 3 percent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.075 | 0.032 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".