MétaCan
Menu
Back to cohort
Record W3092543555 · doi:10.1002/ar.24526

Accurate whole‐mount bone and cartilage staining requires acid‐free conditions

2020· article· en· W3092543555 on OpenAlexafffund
Nicholas W. Zinck, Tamara A. Franz‐Odendaal

Bibliographic record

VenueThe Anatomical Record · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMount Saint Vincent UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStainingBone decalcificationALIZARIN REDCartilageStainChemistryAnatomyBiochemistryPathologyBiologyMedicine

Abstract

fetched live from OpenAlex

Bone and cartilage staining has provided anatomists with the ability to generate detailed descriptions of the adult and developing skeleton. Typically, Alizarin red S and Alcian blue are used for the staining of bone and cartilage, respectively. The binding of Alizarin red S and calcium is most stable at basic conditions, however, Alcian blue exhibits specific binding to polyanionic substances such as mucopolysaccharides under acidic conditions. Typical bone and cartilage staining protocols are conducted under acidic conditions. Because of this discrepancy in optimal pH, issues can arise in the staining of small specimens such as larval fish. Specifically, staining embryonic or larval specimens under acidic conditions can cause decalcification of small bones. Decalcification can completely inhibit the uptake of Alizarin red S in small bones. In order to mitigate this issue, researchers have developed an acid-free staining protocol that utilizes the concept of critical electrolyte concentration. While many researchers have adopted acid-free bone and cartilage staining, some researchers continue to stain these small specimens with acidic staining protocols. To ensure the reliability and validity of our skeletal descriptions, we urge scientists to utilize acid-free staining protocols when analyzing the skeletons of larval or embryonic specimens.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.248
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations11
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueThe Anatomical RecordSame topicFish Ecology and Management StudiesFrench-language works237,207