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Transcranial electrical and magnetic stimulation (tES and TMS) for addiction medicine: A consensus paper on the present state of the science and the road ahead

2019· review· en· W2955210960 on OpenAlexafffund
Hamed Ekhtiari, Hosna Tavakoli, Giovanni Addolorato, Chris Baeken, Antonello Bonci, Salvatore Campanella, Luis Castelo-Branco, Gaëlle Challet‐Bouju, Vincent P. Clark, Eric D. Claus, Pinhas N. Dannon, Alessandra Del Felice, Tess den Uyl, Marco Diana, Massimo di Giannantonio, John R. Fedota, Paul B. Fitzgerald, Luigi Gallimberti, Marie Grall‐Bronnec, Sarah Herremans, Martin J. Herrmann, Asif Jamil, Eman M. Khedr, Christos Kouimtsidis, Karolina Kozak, Evgeny Krupitsky, Claus Lamm, William V. Lechner, Graziella Madeo, Nastaran Malmir, Giovanni Martinotti, William M. McDonald, Chiara Montemitro, Ester Miyuki Nakamura-Palacios, Mohammad Nasehi, Xavier Noël, Masoud Nosratabadi, Martin P. Paulus, Mauro Pettorruso, Basant Pradhan, Samir Kumar Praharaj, Haley Rafferty, Gregory L. Sahlem, Betty Jo Salmeron, Anne Sauvaget, Renée S. Schluter, Carmen S. Sergiou, Alireza Shahbabaie, Christine E. Sheffer, Primavera A. Spagnolo, Vaughn R. Steele, Ti‐Fei Yuan, Josanne D. M. van Dongen, Vincent Van Waes, Ganesan Venkatasubramanian, Antonio Verdejo-García, Ilse Verveer, Justine W. Welsh, Michael J. Wesley, Katie Witkiewitz, Fatemeh Yavari, Mohammad‐Reza Zarrindast, Laurie Zawertailo, Xiaochu Zhang, Yoon‐Hee Cha, Tony P. George, Flavio Frӧhlich, Anna E. Goudriaan, Shirley Fecteau, Stacey B. Daughters, Elliot A. Stein, Felipe Fregni, Michael A. Nitsche, Abraham Zangen, Marom Bikson, Colleen A. Hanlon

Bibliographic record

VenueNeuroscience & Biobehavioral Reviews · 2019
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsUniversité LavalCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchNational Institutes of HealthBundesministerium für Bildung und ForschungDepartment of Science and Technology, Ministry of Science and Technology, IndiaZonMwNational Institute on Alcohol Abuse and AlcoholismDeutsche Forschungsgemeinschaft
KeywordsNeuromodulationTranscranial magnetic stimulationAddictionNeuroscienceEnthusiasmBrain stimulationDeep brain stimulationPsychologyMedicineEngineering ethicsDiseaseParkinson's diseaseEngineeringStimulationPathologySocial psychology

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)0.003
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.171
GPT teacher head0.386
Teacher spread0.215 · 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
GenreReview

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

Citations301
Published2019
Admission routes2
Has abstractno

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