Exploring the effects of sea level change on an ancient port city through archaeological discoveries-Poompuhar
Bibliographic record
Abstract
India with its 5000 years history of maritime activity and 6000 km coast has played a major role in commerce and cultural interaction between the East and West. During historical period India had trade and cultural contacts with Egypt, Rome, Greeks, Arabs, China and all most all Southeast Asian countries. The same maritime traditions continued even during the Buddha, the Mauryas, and the Gupta and in later periods. Human settlement depends on the stability of the coast city. The coastline is one of the reason for the development of human civilization. Through this coastline the civilization is transferred from one place to another. There are many indirect references which suggest that the shifting of shoreline was one of the major threats to habitation. Reference in the Literature like Mahabharata and Manimegalai clearly mentioned the migration of shoreline and associated effects, which has an impact on the human settlement.This paper deals with the archaeological evidences of shoreline shift on east coast of India by collecting the underwater data and to find out the submerged extension of the ancient town of kaveripoompattinam and how much it was swallowed by the sea. Onshore exploration in poompuhar and surrounding sites, particularly in vanagiri were conducted as an evidence many archaeological remains exist all along its coast. Offshore exploration is also conducted and the old coastline is found which indicates clearly the shoreline shift.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".