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Record W2032896433 · doi:10.1080/10520290903052899

Nuclear staining with alum hematoxylin

2009· article· en· W2032896433 on OpenAlexaff
BD Llewellyn

Bibliographic record

VenueBiotechnic & Histochemistry · 2009
Typearticle
Languageen
FieldMedicine
TopicBiological Stains and Phytochemicals
Canadian institutionsPositive Living North
Fundersnot available
KeywordsMordantH&E stainStainingStainAlumChemistryEosin YNuclear chemistryNatural dyePathologyBiochemistryOrganic chemistryMedicineDyeingPhotocatalysis

Abstract

fetched live from OpenAlex

The hematoxylin and eosin stain is the most common method used in anatomic pathology, yet it is a method about which technologists ask numerous questions. Hematoxylin is a natural dye obtained from a tree originally found in Central America, and is easily converted into the dye hematein. This dye forms coordination compounds with mordant metals, such as aluminum, and the resulting lake attaches to cell nuclei. Regressive formulations contain a higher concentration of dye than progressive formulations and may also contain a lower concentration of mordant. The presence of an acid increases the life of the solution and in progressive solutions may also affect selectivity of staining. An appendix lists more than 60 hemalum formulations and the ratio of dye to mordant for each.

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: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0470.019

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 head0.008
GPT teacher head0.235
Teacher spread0.228 · 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
GenreEmpirical

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

Citations99
Published2009
Admission routes1
Has abstractyes

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