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Record W4230536210 · doi:10.1007/978-90-481-9751-4_339

Single-Cell Impedance Spectroscopy

2012· book-chapter· en· W4230536210 on OpenAlexaff
Yimei Zhu, Hiromi Inada, Achim Hartschuh, Shi Li, Ada Della Pia, Giovanni Costantini, Amadeo L. Vázquez de Parga, Rodolfo Miranda, Antoine Barbier, Cristian Mocuta, Rachid Belkhou, Bharat Bhushan, J. H. Hoo, K. S. Park, R. Baskaran, K. F. Böhringer, Wei Lü, Michael Nosonovsky, Moon‐Ho Ham, Ardemis A. Boghossian, Jong Hyun Choi, Michael S. Strano, Amy Lang, María Laura Habegger, Philip Motta, Thomas Bachmann, Hermann Wagner, Donald W. Brenner, Jian Chen, Nika Shakiba, Qingyuan Tan, Yu Sun, Julia R. Greer, M. Laver, S. M. Khaled, Alessandro Parodi, Ennio Tasciotti, Bakul C. Dave, Sarah B. Lockwood, Claudia Musicanti, Paolo Gasco, Fritz Vollrath, Alexander Booth, Andy C. McIntosh, Novid Beheshti, Richard Walker, Lars Uno Larsson, Andrew Copestake, Hyundoo Hwang, Yoon‐Kyoung Cho, Michael Chu, Cláudia R. Gordijo, Xiao Yu Wu, Mathias Kolle, Ullrich Steiner, Szu‐Wen Wang, Frederik Ceyssens, Robert Puers, Xiaodong Han, Shengcheng Mao, Ze Zhang, Lei Jiang, Ling Lin, Regina Ragan, Vanni Lughi, Carlos Drummond, Marina Ruths, Weiqiang Mu, J. B. Ketterson, Pierre Berini, Ya‐Pu Zhao, Fengchao Wang, Shaurya Prakash, Simon J. Henley, José V. Anguita, S. Ravi P. Silva, Munish Chanana, Cintia Mateo, Verónica Salgueiriño, Miguel A. Correa‐Duarte, Swastik Kar, Saikat Talapatra, Javier Calvo Fuentes, J. Rivas, M. Arturo López‐Quintela, Soichiro Tsuda

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDielectric spectroscopyMaterials scienceSpectroscopyElectrical impedancePhysicsEngineeringElectrical engineeringAstronomy

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)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.016

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 head0.017
GPT teacher head0.186
Teacher spread0.169 · 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
GenreMethods

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
Published2012
Admission routes1
Has abstractno

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