Business dynamics – A core and alternative technologies in car Air-conditioning sector under Montreal Protocol: An Indian perspective
Bibliographic record
Abstract
As a signatory to the Montreal Protocol (MP), Indian Refrigeration & Air-conditioning (RAC) sector is undergoing change along with the requirement set by the world environment agencies. Out of which motor vehicle air conditioning systems, or (MVACS) for car industry in India has undergone a major uphill due to increasing environmental consciousness, the use of Chlorofluorocarbons (CFCs), in new as well as in in-use units has been phased out. As it has been observed that the MVACS car service sector is partially found organised and unorganised sector both. In the present work an analysis of critical parameters for implementation of alternative refrigerant technology in Car Air-conditioning has been studied and recommended under Montreal Protocol. The modified idea behind is to highlight on the parameters selected from the respondents based on experts and pioneers of the field. The other parametric approach was on the selection of response strategies based on the methodology of Interpretive Structural modeling (ISM). The structure questions were based on closed type and the communication medium through personal interview & email. About 10 respondents were selected from researchers and various experts from car air-conditioning industry of various positions in their department in India. The result obtained from the respondent is incorporated along with the fact that the economic growth of Indian RAC sector and Indian Research and Development (R&D) division in MVACS-how is getting influenced and used as alternative means, a diagnostic studies is followed.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".