MétaCan
Menu
Back to cohort
Record W4391242799 · doi:10.1097/dcc.0000000000000629

Thank You, DCCN 2023 Peer Reviewers

2024· article· en· W4391242799 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDimensions of Critical Care Nursing · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Once again, we offer our sincere gratitude to our dedicated peer reviewers who validate the true measure of a professional. They contribute to our knowledge-based profession in a unique way. Peer reviewers donate their time and expertise as unpaid volunteers who balance work-life responsibilities exceptionally well. This group of experts guide our authors and helps our journal maintain a level of excellence. Michael D. Aldridge, MSN, RN, CNS, CNE, Austin, Texas Katherine Alford, MSN, RN, CCRN, PCCN, San Antonio, Texas Linda Baas, PhD, RN, ACNP, CCNS, Harrison, Ohio Stefano Bambi, PhD, RN, CCN, Florence, Italy Cathy Bays, PhD, RN, Louisville, Kentucky Ashley Blatchley, MSN, RN, CNML, Portland, Oregon Leanne Boehm, PhD, RN, ACNS-BC, Nashville, Tennessee Shannon Johnson Bortolotto, MS, RN, Aurora, Colorado Helene Bowen-Brady, DNP, MEd, RN-BC, NEA-BA, Walpole, Massachusetts Emmanuele Buccione, MScN, Pescara, Italy Melissa Burton, RN, CCRN, Boston, Massachusetts Glen Carlson, MSN, RN, Kalamazoo, Michigan Rose Constantino, PhD, JD, RN, FAAN, FACFE, Pittsburgh, Pennsylvania Kathleen Costello, BSN, RN, Boston, Massachusetts Jeni Colarusso, BSN, RN, CCRN-K, Salt Lake City, Utah Rhonda Cornell, DNP, APRN, CNP, Mankato, MN Janet T. Crimlisk, DNP, RNCS, NP-C, Boston, Massachusetts Sherill Cronin, PhD, RN, BC, Louisville, Kentucky Kimberly Curtin, DNP, APRN, Houston, TX Brigitte S. Cypress, EdD, RN, CCRN, Pocono Summit, Pennsylvania Jenna Davis, PhD, RNC-NIC, York, Pennsylvania Julianne Evers, DNP, RN, APRN, AGACNP-BC, Louisville, Kentucky Anna Christine Fisk, PhD, RN, Boston, Massachusetts Kathleen Ahern Gould, PhD, RN, Duxbury, Massachusetts Angelica Nicolina Ferrazzi, DNP, MSN, RN-BC, CMSRN, Washington, DC Judy M. Hayes, MSN, RN, NEA-BC, Boston, Massachusetts Kathleen Haubrich, PhD, RN, Hamilton, Ohio Elizabeth K. Herron, PhD, RN, CNE, Harrisonburg, Virginia Cheryl Hines, EdD, MSN, CRNA, Tuscaloosa, Alabama Rosemary Hoffman, PhD, RN, Pittsburgh, Pennsylvania Bonnie Holaday, DNS, RN, FAAN, Clemson, South Carolina Susan Hurst, MSN, RN, CCRN, CNRN, Phoenix, Arizona Jen Hershey, DEd, MSN, RN, CNE, Lancaster, Pennsylvania Chad Johnson, MSN, RN, Thunder Bay, Ontario, Canada Melissa Bailey Johnson, MSN, RN, Philadelphia, Pennsylvania Linda Jean Josephson, MS, RN, Worcester, Massachusetts Linda Kramer, MSN, RN, CCRN, Louisville, Kentucky Kholoud Khalil, PhD, RN, CCRN, Long Beach, California Stacy Kram, MS, RN, Queen Anne, Maryland Ann Harrington Lalor, BSN, RN, Tacoma, Washington Jennifer Lanter, MSPH, RN, Columbus, Ohio A. Renee Leasure, PhD, RN, CCRN, Oklahoma City, Oklahoma Judith Lindsay, PhD, RN, Round Rock, Texas Robin Lockhart, MSN, RN, Wichita Falls, Texas Alberto Lucchini, RN, Monza, Italy Marta Makielski, MN, RN, CCRN Alumnus, South Bend, Indiana Mary E. Mather, MSN, RN, Castroville, Texas Jen Manganello, MSN, RN, ACNP-BC, Farmington, New Mexico Maximino Martell, Madisonville, Los Angeles Virginia Mason, PhD, RN, Milton, Massachusetts Natalie Susan McAndrew, PhD, MSN, Milwaukee, Wisconsin Colleen McCracken, MSN, RN, CMSRN, CHPN, OCN, Milwaukee, Milton, Wisconsin Vickie A. Miracle, EdD, RN, CCRC, Louisville, Kentucky Angela Wang Nguyen, MSN, AGACNP-BC, CCRN, Philadelphia, Milton, Pennsylvania Sharon C. O'Donoghue, DNP, RN, Boston, Massachusetts Ricardo Padilla, PhD, MSN, RN, San Diego, California Mauro Parozzi, PhD, MSN, RN, Milan, Italy Barbara Phelan, PhD, MSN, RN, Bethany, Connecticut Darlene Petersen, MSN, RN, CCRN, CCNS, Gulfport, Mississippi Kelly Powers, PhD, RN, Charlotte, North Carolina Donna Pineau, PhD, RN, CNE Duxbury, Massachusetts Carmen Rosa Presti, DNP, APRN, ACNP-BC, Coral Gables, Milton, Florida Ellen Redick, MSN, MEd, RN, CNA, CPHQ, Miami, Florida Ruthie Robinson, PhD, RN, FAEN, CNS, CEN, Beaumont, Texas Patricia Reilly, MSN, RN, Centerville, Milton, Massachusetts Lisa Ruth-Sahd, DEd, RN, CEN, CCRN, York, Pennsylvania Erica Sciarra, DNP, RN, APN-C, CCRN, Howell, New Jersey Amanda Shrout, MSN, RN, CCNS, CEN, Lancaster, Pennsylvania Gayle Sturgis, RN, Paul's Valley, Oklahoma Nancy Steffan, PhD, RN, CCRN, CRNP, Lewisville, North Carolina Marion Taylor, MSN, RN, FNP-BC, Los Angeles, California Linda Teplitz, PhD, RN, CCRN, Palos Park, Illinois Carolyn Tennyson DNP, ACNP-BC, AACC, CHSE, Durham, North Carolina Elizabeth Thompson, MBA, BSN, RN, CCRN, Lancaster, Pennsylvania K. Renee Twibell, PhD, RN, Muncie, Indiana Patricia Tuite, MSN, RN, CCRN, Pittsburgh, Pennsylvania Linda Weston Tuttle, MSN, RN, CCRN, Louisville, Kentucky Reba A. Umberger, PhD, RN, CCRN-K, Memphis, Tennessee Mary Lou Warren, DNP, RN, Houston, Texas David Woodruff, PhD, APRN, CEN, CCRN-K, FNAP, Downers Grove, Illinois John J. Whitcomb, PhD, RN, CCRN, FCCM, Clemson, South Carolina Marlot Wigginton, MN, RN, ARNP, CCRN, CCNS, Louisville, Kentucky Paula Wolski, MSN, RN-BC, Boston, Massachusetts Nancy York, PhD, RN, Louisville, Kentucky We continue to support all professionals who wish to learn more about the peer-review process. Wolters Kluwer offers engaging and comprehensive training programs for nurses who would like to become a peer reviewer. The courses are also useful for experienced reviewers who would like to extend and update their skills. The course can be accessed at https://wkauthorservices.editage.com/peer-reviewer-training-course/. This site, sponsored by Wolters Kluwer, offers a basic and advanced course; the basic course is free to all users and includes the following: Three-hour interactive e-learning course (6 modules), including videos and quizzes Discussion forum for Q&A Downloadable peer-review report template Downloadable tools and checklists for different stages of reviewing Methodology and statistics reviewing guide by expert peer reviewers Advanced tips to boost your stature. Practice review assignment with assessment and feedback from course faculty Certificate of completion

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.

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)0.003
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.879
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.118
GPT teacher head0.487
Teacher spread0.369 · 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