Evaluation and optimization of acid processing procedures for the extraction of conodont elements from calcareous rock
Bibliographic record
Abstract
The purpose of this study was to identify alternative methods which would improve current conodont processing times and cost at the GSC-Calgary paleontology lab. Conodont processing consists of several stages, most of which are completed within a single day. Acid digestion, however, is the longest processing stage and is also conveniently the most variable in terms of processing techniques. Therefore, this is where this study seeks to improve. The current sample digestion technique utilizes an acetic acid solution which take a notably long time to completely process samples therefore, investigation into quicker techniques commonly used in other labs utilizing formic acid were explored. Formic acid processing improved digestion time to 3 days compared to acetic acid processing's maximum of 56 days. Processing cost results favored acetic acid which totaled $126.41 for full processing of 2.5kg samples, compared to formic processing cost of $101.73 for 1.0kg of sample which theoretically totals $127.99 per 2.5kg of sample. Lab productivity significantly improved using formic acid, capable of producing 350 samples per year opposed to 195 samples processed via acetic acid. Observing extracted specimen under a scanning electron microscope showed no difference between the processing methods. Both methods could produce pristine sample quality which was completely indistinguishable. Based on these findings, the formic acid processing method can be used as a viable technique for the extraction of conodonts from calcareous rock and should be offered as a fast-track, but slightly more expensive alternative for sample processing.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 teacher head, 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".