Characterization of the stem anatomy of the Eocene fern <i>Dennstaedtiopsis aerenchymata</i> (Dennstaedtiaceae) by use of confocal laser scanning microscopy
Bibliographic record
Abstract
PREMISE OF THE STUDY: Permineralization provides the most faithful known mode of three-dimensional preservation of the morphology and cellular anatomy of fossil plants. Standard optical microscopic documentation of such structures can provide only an approximation of their true three-dimensional form and is incapable of revealing fine-structural (<300 nm) details, deficiencies that can be addressed by the use of confocal laser scanning microscopy (CLSM). METHODS: To demonstrate the usefulness of CLSM in such studies, we compare confocal laser scanning micrographs and optical photomicrographs of the permineralized tissues of rhizomes and petioles of the Eocene fern Dennstaedtiopsis aerenchymata preserved in cherts of the Clarno Formation of Oregon, USA, and the Allenby Formation (Princeton chert) of British Columbia, Canada. KEY RESULTS: The laser-induced fluorescence detected by CLSM produces crisp high-resolution images of the three-dimensionally permineralized tissues of Dennstaedtiopsis aerenchymata. Tissues analyzed include the epidermis and epidermal hairs, cortex, aerenchyma, endodermis, vascular tissue, and pith-for each of which, CLSM yields results superior to those of standard optical microscopy. CLSM and previous Raman spectroscopic analyses of the same specimens provide evidence consistent with original biochemistry. CONCLUSIONS: Use of CLSM to characterize the morphology and cellular anatomy of permineralized fossil plants can provide accurate data in two and three dimensions at high spatial resolution, information that can be critically important to taxonomic, taphonomic, and developmental interpretations. Results presented here from this first detailed CLSM-based study of permineralized plant axes indicate that this nonintrusive, nondestructive technique should be widely applicable in paleobotany.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".