Bibliographic record
Abstract
A set of about 2,000 historical maps of South Asia produced by the Survey of India, at a scale of 2 miles per inch (1:126,720). These maps cover the territory from Eastern Persia (Iran) through present day Afghanistan, Pakistan, India and Burma, and in general were produced during the first half of the 20th century. Each map is a half degree wide by a half degree high, and thus covers the area of one quarter of a 1 degree x 1 degree block. The file naming convention is to first give the number of the 4 degree x 4 degree block followed by the letter (A to P) of the sixteen 1 degree x 1 degree blocks in each 4 degree block, followed by the designation NE, NW, SE or SW to designate one of the four quarters of the one degree block--eg. 38 D SW. This is followed by the name of a town or geographical area encompassed by the map, followed by the date of publication in parenthesis. If a map is reprinted without changes sometime after its initial publication, it is the date of initial publication that is used. An Index Map with the title "0 Topographical Indexes of Survey of India 253k and 126k" showing the sheet numbering system is provided as the first entry in the list of files. This index map can be downloaded to assist in selecting particular maps of interest to the viewer. The maps are then listed in numerical order by sheet number. More than one map will be shown for each geographic block when maps with different publication dates are available. The viewer may find it convenient to use the Search Function (Windows: Ctrl F or Mac: Cmd F) to quickly navigate to a particular map of interest. A click on the "Preview" button will open a preview image, but it will be located at the very top of the file list. A click on the "Download" button will download the map file to the viewer's computer. The map scans are collected from many sources, and the quality of the scans as well as the underlying paper maps is uneven. Some scans are professionally done, while others are of poor quality. On the assumption that 'some map is better than no map,' we include the poor quality scans until a better copy can be obtained.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.018 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.330 | 0.138 |
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".