New Year greetings from PETROTECH SOCIETY!
Bibliographic record
Abstract
An eventful year 2008 has just gone by! This special issue of inhouse journal coincides with the biennial mega event. Under your continued patronage, several new initiatives have been taken during the year to improve the overall stature of the Society. Some of these initiatives are listed below for your kind appreciation. Going Global: A small beginning has been made by signing a formal MoU with University of Alberta, Canada and holding preliminary discussions with Sinopec Management Institute China for developing mutual areas of co-operation. Efforts will continue to bring PETROTECH Society in the international arena by building up relationships with many such international bodies in the coming year. Industry Awareness Programme : As part of our two pronged strategy, many industry experts have visited various institutes/ universities to deliver hands-on type talks to fi nal year students. This has been well received by the institutes and student community. Besides the above, a 14 member group of Industry experts alongwith Govt of India representative (Mr Lal Chhandama, under Secretary in MoP&NG) visited Canada under the banner of PETROTECH Society, where they were apprised about the advancements made by Canadian Hydrocarbon Industry. This was a good educational tour appreciated by all participants. Student Chapters: In order to reach out to the student community studying petroleum engineering subjects, the Society
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.525 | 0.327 |
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; the direct Gemma label and the distilled Codex classifier 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".