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Record W4212837855 · doi:10.1109/icmla.2019.00006

Program Committee and Reviewers

2019· article· en· W4212837855 on OpenAlexaff
Tiago A. Almeida, Khaled Mohamed, Saeed Alahmari, Plamen Angelov, Danielle Apiletti, Juan Carlos Manrique Arribas, Thomas Bäck, Arunkumar Bagavathi, Ajay Bansal, Adrian S. Barb, Penn State, Great Valley, Gustavo Batista, Richard A. Bauder, Abdelhamid Bouchachia, Nizar Bouguila, Paula Branco, George Bravos, Robert A. Bridges, Glenn Bruns, Murillo G. Carneiro, Gabriel Castaneda, Kyle Caudle, Philip K. Chan, Chanda Pramit, Dechang Chen, Bernard Chen, Bilian Chen, Ching‐Hua Chuan, Mohammad Reza Daliri, Vincenzo De Maio, Alex Delis, Anne Denton, Zhengming Ding, Fernandes Fabiola, Minghong Fang, Elaine R. Faria, Daniele Foroni, Jun Gao, Fernando Gomide, Jie Gui, Armin Haller, Jonathon Hare, Murtadha D. Hssayeni, Changwei Hu, Yuh-Jong Hu, Xiaodi Huang, Jens Hülsmann, Faraz Hussain, Ali Idri, Mohamed University, Mohammad Khairul Islam, Virginia Tech, Mohit Jain, Morgan Chase, Ahmad Y. Javaid, Alokkumar Jha, Haoming Jiang, Xiaoyi Jiang, Peiquan Jin, Ruoming Jin, Justin Johnson, Paul D. Kennedy, Natalia Khuri, Taghi M. Khoshgoftaar, Sun Kim, Kamran Kowsari, Srdjan Krco, Alina Dunavnet, R.E. Leon, Li Liao, Erik Linstead, Tianyi Liu, Hongfu Liu, Feng Liu, Chunmei Liu, Darrell D. E. Long, Edwin Lughofer, Feng Luo, Bo Luo, Ramesh Maddula, Pedroto Facebook, Maryam Maria, Enzo Najafabadi, Radhakrishnan Nagarajan, Giri Narasimhan, Daniel Neagu, Wilfred Ng, Ming Ni, Alexandros Ntoulas, Zynga Ofoghi, Mitsunori Ogihara, Ahmet Ozcan, Suat Özdemi̇r, Gazi Üniversitesi, Carlos Paradis, Vitor Pires, Seyedamin Pouriyeh, Radu‐Emil Precup, Tieyun Qian, Guangzhi Qu, Adıń Ramıŕez Rivera, Pranav Raval, Christian Gtu, Daniel Rodríguez, Samira Sadaoui, Serap Sahin, Daniel Sánchez, Miguel A. Sanz‐Bobi, Johannes Schmitt, Sevil Şen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsUniversity of ReginaDalhousie University
Fundersnot available
KeywordsComputer science

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)0.036
metaresearch head score (Gemma)0.156
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.769
Threshold uncertainty score0.774

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.156
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.003
Science and technology studies0.0040.001
Scholarly communication0.0080.003
Open science0.0030.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.2310.193

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 head0.015
GPT teacher head0.259
Teacher spread0.245 · 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.

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractno

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