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Record W3112766701 · doi:10.1097/pai.0000000000000893

A New Pair of Shoes

2020· editorial· en· W3112766701 on OpenAlexaboutno aff
Paul E. Swanson

Bibliographic record

VenueApplied immunohistochemistry & molecular morphology · 2020
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsExcellenceReputationResource (disambiguation)Editorial boardComputer scienceLibrary sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Change, though inevitable, can be welcomed as a challenge. In April of 2020, Drs Clive Taylor and Jiang Gu stepped down from their roles as Editors in Chief of this journal. Dr Taylor, who founded Applied Immunohistochemistry in 1993 as the published voice of its sponsoring society, the Society for Applied Immunohistochemistry, and Dr Gu, who developed the journal Cell Vision: Journal of Analytic Morphology in 1994, shared a vision of a publication that would be the journal of choice for those of us interested in immunohistochemistry and morphology-based molecular assays in diagnostic pathology. Through the merger of their journals, first published together in 1999, what we now know as Applied Immunohistochemistry and Molecular Morphology was borne. This journal has been an important resource for investigators and diagnosticians alike and has earned a reputation for excellence under their guidance. With their departure (though they have only travelled a small distance down the masthead, since they remain with the journal as Senior Associate Editors), there seem to be some rather large shoes to fill. I am honored to be able to take on (and hopefully improve upon) their shared vision at a time when morphology based diagnostic and predictive assays are becoming increasingly sophisticated surrogates for true molecular techniques. This is my challenge, but is also my challenge to you, as readers of this journal. Collectively, we have the opportunity to expand the influence of our journal by highlighting the best current work in the field, but also by incorporating new approaches to the practice of immunohistochemistry and molecular morphology. I take this role seriously, knowing that each of you have options both among resources for information pertinent to your practice but also as a place to present your newest ideas and findings to your peers. But to continue to make AIMM your journal of choice, it will take more than an effort to fill another’s shoes. This job requires an entirely new set of shoes. We will continue to focus on novel observations with immediate diagnostic applications in both immunohistochemistry and molecular morphology, but we will also seek descriptions of relevant animal models of human disease that can foster clinical investigations that will improve the contributions of immunohistochemical and molecular analyses to those diseases. AIMM can and should continue to be a resource for best practices in assay validation and performance through insights and guidelines from experts. But I would also like to augment the role of this publication as the venue of choice for the emphasis of important concepts through meaningful and timely review papers. Finally, this should be the place for novel applications of immunohistochemistry and molecular morphology as seen through the lens of artificial intelligence and machine learning. I look to members of our sponsoring society, the International Society for Immunohistochemistry and Molecular Morphology, as a vital reservoir of experience and insight in these matters, and welcome novel studies from all interested parties to further these goals. To assist me in this mission, I have recruited 2 new Associate Editors: Dr Emina Torlakovic (University of Saskatchewan) will help guide us to improvements in the quality of editorial review and manuscript content, and will also help bring issues related to assay validation and performance into clearer focus; and Dr Andrew Bellizzi (University of Iowa) will work with our editorial board and our readers to develop a robust slate of pertinent and practical reviews. In addition, I will rely on all members of our Associate Editor team to work on special projects that will, from time to time, allow us to present issues devoted in part to important topics in diagnostic surgical pathology practice. Look for an example of this approach in our next issue. Importantly, I also intend to expand the reach of the journal by developing a robust social media presence for both editorial board members and readers alike, with an eye to improving awareness of journal content among those in academic and community practice. To that end, we have recruited Dr Matthew Gosse at the University of Iowa to spearhead that effort as our first social media editor. He will introduce you to that effort (and links to his postings) in the commentary that follows these remarks. As we look to the future of the journal, I must again pay tribute to those who have guided the journal to its present state. I plan to work with our editorial team to develop a set of papers for AIMM that honor the contributions of both Dr Taylor and Dr Gu to our special field of inquiry. I also thank Dr Richard Cote and Dr Lawrence Weiss for their service to the journal as Associate Editors and look forward to their continuing contributions to AIMM as members of our editorial board. Finally, I must note, with great sadness, the recent passing of Dr Juan Rosai. As a sign of my great admiration for him both personally and as a driver of remarkable change in surgical pathology, I have kept him on our masthead through this issue in honor of his immense impact on immunohistochemistry and its place in diagnostic surgical pathology. His way of looking at immunohistochemistry and how that insight materially changed how we practice will be sorely missed. So, time to move forward. I welcome your thoughts on how this journal can best serve your practice needs and I look forward to working with you and our editorial board to bring you the best this field can offer.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.115
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0030.001
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 head0.007
GPT teacher head0.262
Teacher spread0.256 · 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
GenreEditorial

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
Published2020
Admission routes1
Has abstractyes

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