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Record W2063548382 · doi:10.1309/ajcpvbzz4ikjhy3u

An Improved Processing Method for Breast Whole-Mount Serial Sections for Three-Dimensional Histopathology Imaging

2009· article· en· W2063548382 on OpenAlexaff
Laibao Sun, Dan Wang, Judit Zubovits, Martin J. Yaffe, G. Clarke

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2009
Typearticle
Languageen
FieldComputer Science
TopicAI in cancer detection
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsFixation (population genetics)HistopathologyPathologyMedicineBiomedical engineering

Abstract

fetched live from OpenAlex

To develop and validate improved processing methods for producing diagnostic-quality, whole-mount serial sections for 3-dimensional imaging of whole-breast histopathologic studies, we subjected 4-mm-thick whole-specimen slices to a 38-hour microwave-assisted protocol. Morphologic features, antigenicity, and tissue shrinkage were evaluated. A schedule using the tissue processor was optimized by evaluating the serial section yield for 3 schedules. The microwave-based processing schedule is adequate for producing diagnostic-quality whole-mount breast serial sections of an area up to 6,000 mm(2) and is compatible with a variety of immunohistochemical stains. A mean +/- SE total tissue shrinkage of 8.4% +/- 0.2% resulted. For the tissue processor, optimal results are obtained using a 59-hour schedule. Total fixation and processing time for whole-mount serial breast sections has been reduced from 21 days to 38 hours, with microwave assistance, and to 59 hours without. No adverse effects of microwaves on morphologic features, antigenicity, or gross tissue dimensions were observed.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.028
GPT teacher head0.402
Teacher spread0.375 · 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 designBench or experimental
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

Citations30
Published2009
Admission routes1
Has abstractyes

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