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Record W2465745209 · doi:10.1111/add.13353

Correcting the record on NCRG‐funded research

2016· letter· en· W2465745209 on OpenAlexaffabout
Linda B. Cottler, Tammy Chung, David C. Hodgins, Miriam Jorgensen, Gloria M. Miele

Bibliographic record

VenueAddiction · 2016
Typeletter
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsLibin Cardiovascular Institute of AlbertaUniversity of Calgary
FundersNational Center for Responsible Gaming
KeywordsAcknowledgementMillerPopulationSection (typography)Library scienceSample (material)Research centerPolitical sciencePsychologyMedicinePublic relationsMedical educationLawSociologyComputer scienceBusinessDemographyAdvertising

Abstract

fetched live from OpenAlex

We are writing to respond to an editorial in Addiction 1 that made reference to the National Center for Responsible Gaming (NCRG) and its research grants program. The editorial is misleading, as it provides a mischaracterization of our program. We are responding to provide a realistic picture of NCRG. When discussing NCRG-funded publications in their essay, Babor & Miller state that ‘fewer than half (48%) cited funding from the NCRG in their Acknowledgement section or in a footnote of the paper’ (1, p. 341). We were surprised at this low rate of acknowledgement. Consequently, the NCRG staff contacted Dr Babor, who provided a list of the 30 papers included in his study as well as the 173 papers from which the sample of 30 was drawn. We examined the 167 papers from Babor & Miller's population that were immediately available to us and found that 72% of papers acknowledged that funding was provided by NCRG or the correct name of the organization at the time of paper publication. Also, in the past 5 years more than 98% of NCRG-funded papers have been acknowledged correctly. We have included our complete materials supporting the above points for public inspection in the ‘Supporting information’ section of the Journal's website. The claim that ‘fewer than half’ of NCRG-funded papers were acknowledged is not accurate. The actual rate for the history of the organization is more than 70% and more than 98% in the last 5 years. Correcting this misleading claim is important to NCRG, the Scientific Advisory Board and NCRG grantees. The claim leads readers to think mistakenly that NCRG is exerting influence on the science it funds, and that NCRG awardees do not want to divulge the source of funding for fear that their science will not be published. This could not be further from the truth. All authors are members (unpaid) of the National Center for Responsible Gaming Scientific Advisory Board, and receive reimbursement for travel to its annual board meeting, and coverage of hotel expenses to attend the board meeting. L.B.C. is funded by the National Institute on Drug Abuse (NIDA), National Center for Advancing Translational Sciences (NCATS), and the Patient Centered Outcomes Research Institute (PCORI). T.C. is supported by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and National Institute on Drug Abuse. D.C.H. received partial salary support from the Alberta Gambling Research Institute, funded by the Government of Alberta. L.B.C., D.C.H., G.M. and T.C. have served as reviewers for the NCRG competitive grants program, speakers at the NCRG annual conference in Las Vegas or won the NCRG Scientific Achievement Award. The Scientific Achievement Award is selected by a group of independent scientists and does not include any member of the NCRG Board of Directors, Scientific Advisory Board or NCRG staff. Each was compensated at the same rate paid to other reviewers, speakers or award winners. Each individual has received less than $2800 from these activities, in total, during the last 5 years. T.C. has served on the expert panel (unpaid) to develop the NIAAA Practitioner Guide for Alcohol Screening in Youth. D.C.H. has provided occasional, unpaid consultation to government agencies related to his research (e.g. Alberta, Singapore, Victoria). Appendix S1 The NCRG Firewall. Appendix S2 Organizational Nomenclature. Appendix S3 NCRG-Funded Publication Data. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0040.026
Insufficient payload (model declined to judge)0.0090.004

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 head0.728
GPT teacher head0.621
Teacher spread0.107 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations6
Published2016
Admission routes2
Has abstractyes

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