Bibliographic record
Abstract
India, the second biggest country in the world, has nearly 1.25 million people living in 29 states and seven union territories covering an area of 3,287,000 sq. km. India's economy grew at an impressive 8.2% in the first quarter of 2018-19. Traditionally, India has the habit of reuse and recycling the materials wherever possible. As the city agglomeration is increasing the waste generation is increasing. The number of towns/cities have increased from 5,161 in 2001 to 7,935 in 2011, whereas the number of metropolitan cities having million plus population has increased from 35 to 53 number as per 2011 census. It is projected that half of India's population will live in cities by 2050. Waste management in India has been experiencing a paradigm shift through the establishment of Swachh Bharat Mission in urban and rural India in 2014 and the revision and establishment of waste management rules in six types of wastes including transboundary movement in 2016. This study presents the overall waste management scenario and the legal framework in India.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".