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Contributors

2025· book-chapter· en· W4407257954 on OpenAlexaff
Shahrukh Nawaj Alam, Ravi Kumar Asthana, Pawan Baghmare, Prantik Banerjee, Aminu Bature, Dipjyoti Chakraborty, Shivani Chaudhary, Ajay K. Dalai, Charu Deepika, Kshanaprava Dhalsamant, Kakoli Dutt, Ratindra Gautam, Yashveer Gautam, Sushant Gawali, Sachin Rameshrao Geed, Praveen Kumar Ghodke, Indrani Ghosh, Mayurika Goel, Trupti Gokhale, Abhishek Guldhe, Neha Gupta, Rajan Kumar Gupta, Abdul Munaf Mohamed Irfeey, Siddhi Jaiswal, Amit K. Jaiswal, Krishna Kumar Jaiswal, Km Smriti Jaiswal, Radhika Jaithaliya, Jerin James, Zaira Khalid, Valeed Ahmed Khan, Gyanab Konwar, Indrajeet Kumar, Sachin Kumar, Ajay Kumar, Laxmi Kumari, Neda Mehravar, Lynsey Melville, Rajalakshmy Menon, Mrinal, Yogesh Kumar Murugesan, Ashutosh Namdeo, Vivek Kumar Nautiyal, Aditi Nayak, Hettimudalige Dilini Nisansala, Revanth Babu Pallam, Biswa R. Patra, Falguni Pattnaik, Roshni Paul, Hishita Peshwani, Cheryl Bernice Pohrmen, Aneesh Raj, Navnit Kumar Ramamoorthy, Arun Prasath Ramaswamy, Renju, L.M. Rifnas, Gobardhan Sahoo, Ausaf Saleha, V. Venkateswara Sarma, Sivasankari Sekar, Ruplappara Sharath Kumar, Rohit Sharma, Mohamed Aseem Shazahan, A.K. Shinde, Zahra Shokravi, Vanya Shrivastav, Nikhil Kant Shukla, Shagufi Zea Siddiqui, Avinash Singh, Neeraj Kumar Singh, Rahul Prasad Singh, Bhaskar Singh, Monika Singh, Savita Singh, Shruti Singh, Amila Siriwardana, Manoj Kumar Solanki, Sri Suhartini, Michael Sulu, Vishal Thakur, Jitendra Singh Verma, Ajitha Vijjeswarapu, Priya Yadav

Bibliographic record

VenueElsevier eBooks · 2025
Typebook-chapter
Languageen
Field
Topic
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.258
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7420.676

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractno

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