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Record W7098283510

SUMMARY

2015· article· en· W7098283510 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsCollodionGolgi apparatusSilver nitrateEndoplasmic reticulumReticular connective tissueNeurofilament
DOInot available

Abstract

fetched live from OpenAlex

1. It was accidentally found that methods of silvering synaptic end-feet sometimes blackened Golgi's 'internal reticular apparatus ' in neurones of the central nervous system of the cat. 2. A method of achieving this consistently was worked out: (a) paraffin sections are coated with a collodion membrane; (b) the collodion membrane is soaked in silver nitrate; (c) the silver nitrate is reduced to metallic silver with a buffered formaldehyde solution; (d) steps (b) and (c) are repeated until the sections appear quite black; («) the silver attached to structures other than the Golgi apparatus is removed with a ferricyanide/thiosulphate bleach; (/) the section is 'toned ' with gold chloride, fixed in thiosulphate, and washed thoroughly; (g) the section is dehydrated, cleared, and finally mounted in Canada balsam, DPX, or similar media. Results: Golgi-apparatus, black; connective-tissue fibres, black; axons, grey to black; everything else is light grey or colourless. 3. A tentative hypothesis is advanced to explain the results obtained. 4. The following advantages are claimed for the new method: the cytoplasmic reticulum thus blackened resembles that seen in living neurones with the interference microscope; special methods of fixation are not required; the cytoplasmic reticulum of given cells can be studied before and after silvering; and serial sections of the same piece of tissue can be used for histochemical purposes.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.268

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 science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.299
Teacher spread0.269 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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