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Record W2993337825 · doi:10.1115/1.4045590

Professor Jyeshtharaj Bhalchandra Joshi on His 70th Birthday

2019· article· en· W2993337825 on OpenAlexaboutno aff
Mohamed M. Awad, Sanjoy Banerjee, Masahiro Kawaji

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
Fundersnot available
KeywordsAtomic energyLibrary scienceManagementSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

Professor Jyeshtharaj B. JoshiProfessor Jyeshtharaj B. Joshi is one of the well-known names in the fields of chemical and nuclear engineering. He was born on the May 28, 1949, in Masur, Satara, Maharashtra, India. He received his B.E., M.E., and Ph.D. degrees in 1971, 1972 and 1977, respectively, in chemical engineering from the University Department of Chemical Technology (UDCT), presently the Institute of Chemical Technology, Matunga, Mumbai, India. He did his Ph.D. thesis under the supervision of Professor Man Mohan Sharma.After finishing his Ph.D. in 1977, Professor Joshi worked at the UDCT in different positions and retired at the age of 60 as its Director in 2009. During his work at the UDCT, Professor Jyeshtharaj B. Joshi was involved in several activities. For instance, he organized around 200 science workshops within the period 1999–2000. He was one of the key persons for getting the research funds by the way of research contracts, donations, and project consultancies. After his retirement, he joined as a Homi Bhabha Chair Professor in the Homi Bhabha National Institute, Department of Atomic Energy (DAE), Anushaktinagar, Mumbai. Currently, he is working as emeritus professor in the Department of Atomic Energy (DAE), Anushaktinagar, Mumbai.During his academic life at different places in India, Professor Joshi has published several articles, reports, and textbooks on computational fluid dynamics, nuclear reactor design, and multiphase flow such as Refs. [1] and [2]. In the field of nuclear engineering, Professor Joshi has published many articles in the recent years such as Refs. [3–13].Professor Jyeshtharaj B. Joshi has served on the Editorial Advisory Boards of several well-known and peer reviewed international journals like the Canadian Journal of Chemical Engineering, Chemical Engineering Research and Design, Chemical Engineering Science, and Reviews in Chemical Engineering.He is also J.C. Bose Fellow in the Institute of Chemical Technology, Mumbai, Fellow of the Indian National Science Academy (FNA), and Fellow of the Academy for the Developing World (TWAS). In addition, he is the recipient of several national awards such as INSA Medal for Young Scientist in 1981, Amar-Dye-Chem Award for Excellence in Research and Development in 1983 given by the Indian Institute of Chemical Engineers. In 1991, he received The Shanti Swarup Bhatnagar Prize for Science and Technology given by the Council of Scientific and Industrial Research (CSIR), which is named after the founder Director of the Council of Scientific and Industrial Research, Shanti Swarup Bhatnagar. Also, he is the winner of Diamond Award of UDCT in 1994, Viswakarma Medal of INSA in 2000, Indian Institute of Chemical Engineers Award in 2007, and Zyed Hussain Zaheer Medal of INSA in 2008. In 2014, he received the Padma Bhushan award from the former Indian President Pranab Mukherjee, for his services to the field of nuclear science and chemical engineering.On the occasion of his 70th birthday, on behalf of his colleagues, friends, and students all over the world, we wish Professor Jyeshtharaj B. Joshi a continuous active life in happiness and good health and a very happy birthday!

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0550.041

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.

Opus teacher head0.004
GPT teacher head0.192
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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