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Record W4245417838 · doi:10.1002/app.45615

Editorial Board, Aims & Scope, Table of Contents

2017· paratext· en· W4245417838 on OpenAlexaff
Stefan Spiegel, Conor Doss, Jie Cai, Emily Hu, Ying Jia, Jenny Mahoney, Mara Staffilani, Bo Weng, Marc Zastrow, Harini Anandhi, Senthilkumar Assistant, Carla Amador, Katy Miller, Melissa Ekis, Herman Consulting, Eric Baer, Subramanian Iyer, Brian Knapp, Bart Van der Bruggen, Yu‐Zhong Wang, Christoph Weder, Andrew K. Whittaker, Paula M. Wood‐Adams, Kenneth J. Wynne, Lina Zhang, Liqun Zhang, Da Li, Silva And, Bluma G. Soares, Chao Ren, Mao Liu, Jian Zhang, Qichun Zhang, Xiaowei Zhan, Fei Chen, Karuna Mahato, Kaushik Dutta, Balmiki Ray, Lei Feng, Jude O. Iroh, Naseem Iqbal, Deepak Kumar, Papai Roy, T. K. Ravi, S Jabasingh, Giselle Santiago Cabral Raulino, Leonard Da Silva, Carmen Vidal, Elise De, Shayanne Josicleide de Almeida, Dipankar De, Queize Nascimento de Melo, Ribeiro Nascimento, Yong Cai, C Mei, Meiping Guan, Qihui Wu, Xin Sun, B Xu, K Wang, Moovakat Mohamed Rizwan, Rosiyah Yahya, A. Y. Hassan, Muhammad Yar, Rasheed Sayyed Omar, Parviz Azari, Ahmad Danial Azzahari, V Selvanathan, Anis Rageh Al‐Maleki, Gopalakrishnan Venkat‐Raman, Magdalena Kmiotek, D Bieli, Małgorzata Piotrowska, Fati̇h Demi̇rci̇, Kevin Yildirim, Hasan B. Kocer, Rui Li, Xiaoming Cai, Y Ye, Guozhong Wu, Yun Li, Hong Liu, Shiping Zhu, Junliang Guo, Gangui Yan, Lamy Mamdoh Mohamed Hamed

Bibliographic record

VenueJournal of Applied Polymer Science · 2017
Typeparatext
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsScope (computer science)Table of contentsTable (database)Editorial boardCitationComputer scienceWorld Wide WebLibrary scienceInformation retrievalDatabaseProgramming language

Abstract

fetched live from OpenAlex

In a paper by Suming Li and colleagues, poly(e-caprolactone)-poly(ethylene glycol) (PCL-PEG) and poly(ecaprolactone/glycolide)-poly(ethylene glycol) (P(CL/GA)-PEG) diblock copolymers were synthesized as potential drug carriers.Self-assembly of the resulting amphiphilic copolymers yielded spherical or wormlike micelles, depending on the copolymer composition and the hydrophobic block length.Worm-like micelles were exclusively obtained for PCL-PEG, whereas spherical micelles were obtained for P(CL/GA)-PEG copolymers because introduction of glycolide disrupted the chain structure.Encapsulation of paclitaxel was realized in the core of micelles with high drug loading.Prolonged drug release was observed, showing that these micelles could be promising for applications as drug carriers.(DOI: 10.1002/ app.45732)This image from Jianzhong Lou and colleagues shows 0.5 wt % graphene (xGnP-5) coated polypropylene pellets.The pre-calculated amount of graphene was first dispersed in isopropyl alcohol (IPA) by magnetic stirring.Then, the required amount of polypropylene pellets was added to the graphene/IPA solution and sonicated.Finally, solvent was evaporated to obtain graphene-coated polypropylene pellets.Compression molding of graphene-coated polymer pellets resulted in electrically conductive material as the graphene coating formed a continuous network.(

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)0.006
metaresearch head score (Gemma)0.026
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 score0.737
Threshold uncertainty score0.880

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.002
Science and technology studies0.0030.001
Scholarly communication0.0150.005
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.2630.238

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 head0.041
GPT teacher head0.251
Teacher spread0.210 · 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".

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Citations0
Published2017
Admission routes1
Has abstractno

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