Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In 1961 the Government of India appointed a Standing Commission for Scientific and Technical Terminology to formulate principles for evolution of terminology and preparation of standard textbooks in Hindi and other Indian Languages. The Commission published several glossaries of Engineering terminology, but none of mining engineering. From 1943 to 1954, Professor Raghu Vira, the noted Indian linguist, also published quite a few special dictionaries, and for the first time collected and compiled some mining terms in his Comprehensive English-Hindi Dictionary (1981). Though these indicate a first positive move toward collecting, processing and disseminating specialised vocabularies, their authors' principles and methods of developing terminologies vary. For want of a standard terminology of mining in Hindi and a lack of understanding of terminological concepts and their interrelationships, no textbook of mining could be written in or translated into Indian languages. It is also realised that translation of mining literature should be done by mining engineer translators who understand the systems of concepts, systems of terms and principles of translation. For a wider dissemination of scientific knowledge and technical skills, development of terminologies in Indian languages on internationally accepted sound terminological principles is necessary, even though presently subject specialists communicate in English. With the present government formulating programmes to use on a large scale the new communication technology in our school system, teaching of terminology within the framework of ESP syllabus at undergraduate level is also suggested.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it