Bibliographic record
Abstract
India's growing prominence in global supply chains is driven by its strategic location, large labor force, and government initiatives. The country's economy has demonstrated remarkable resilience, achieving an annual GDP growth of 8.15% for the fiscal year 2023-2024. With its robust domestic consumption, manufacturing expansion, and infrastructure development, India is poised to become a pivotal player in global supply chains. This paper discusses India's evolving role in global supply chains, highlighting key factors driving its growth, government initiatives, challenges, and opportunities. India's GDP growth rate is projected to be around 6.7% in 2025, driven by strong domestic demand and robust GST reforms. The economy has shown resilience, with a growth rate of 7.8% in the April-June quarter of 2025, the fastest in five quarters. Here's a breakdown of the growth projections. India has recorded a trade deficit with nine of its top 10 trading partners in FY 2023- 24.The country is working to diversify its trade relationships and strengthen economic ties with key partners. India's export growth potential is vast, with projections indicating a significant increase in exports driven by various factors. Key highlights include.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 0.016 |
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".