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Record W2890196271 · doi:10.1039/c8fd90024h

Processes at nanoelectrodes: general discussion

2018· article· en· W2890196271 on OpenAlexaff
Hassan Alzahrani, Christophe Antoine, Koichi Aoki, Lane A. Baker, Sébastien Balme, Cameron L. Bentley, Gourav Bhattacharya, Paul W. Bohn, Qiong Cai, Chan Cao, Daniël Commandeur, Richard M. Crooks, Martin A. Edwards, Andrew G. Ewing, Kaiyu Fu, Alina Galeyeva, Rui Gao, Thomas J. P. Hersbach, A. Robert Hillman, Yong-Xu Hu, Lei Jiang, Frédéric Kanoufi, Christine Kranz, Shaochuang Liu, Tobias Löffler, Yi‐Tao Long, Julie V. Macpherson, Kim McKelvey, Shelley D. Minteer, Michael V. Mirkin, Andrew R. Mount, Richard J. Nichols, Wojciech Nogala, Denis Öhl, Kaipei Qiu, Hang Ren, Jennifer A. Rudd, Wolfgang Schuhmann, Zuzanna S. Siwy, Zhong‐Qun Tian, Patrick R. Unwin, Yixian Wang, Patrick Wilde, Yanfang Wu, Zhugen Yang, Yi‐Lun Ying

Bibliographic record

VenueFaraday Discussions · 2018
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of TorontoCanada Research ChairsKensington Health
FundersEngineering and Physical Sciences Research Council
KeywordsNanotechnologyData scienceComputer scienceMaterials science

Abstract

fetched live from OpenAlex

Yitao Long opened the discussion of the paper by Lei Jiang:This paper was not presented; questions on this paper were communicated after the meeting. This work is a very good example of your recently proposed ‘quantum-confined superfluid’ concept – it is really imperative to fabricate ion chann

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.008
GPT teacher head0.253
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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations3
Published2018
Admission routes1
Has abstractyes

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