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A simple method for SEM examination of sectioned diatom frustules

2001· article· en· W1530772183 on OpenAlexaff
Guillaume Massé, M. Poulin, Simon T. Belt, J. ‐M. Robert, A. Barreau, Yves Rincé, Steve Rowland

Bibliographic record

VenueJournal of Microscopy · 2001
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsCanadian Museum of Nature
Fundersnot available
KeywordsDiatomUltrastructureTransmission electron microscopyScanning electron microscopeMaterials scienceFrustuleNanotechnologyBiologyAnatomyComposite materialEcology

Abstract

fetched live from OpenAlex

We describe an innovative yet straightforward method to obtain high quality thin sections of diatom exoskeletons for observation by scanning electron microscopy (SEM). The use of this new technique allows for clear observations of some ultrastructural valve features, including the raphe, which are generally difficult to observe and describe accurately using transmission electron microscopy analysis of thin sections or SEM of randomly fractured diatom valves. In addition, because this method involves the complete removal of the organic content of the diatom cells, resulting in clean and mostly undisturbed skeletal thin cross-sections, even the intact valvar structures of weak girdle bands can be studied.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.025
GPT teacher head0.368
Teacher spread0.342 · 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 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

Citations18
Published2001
Admission routes1
Has abstractyes

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