AN EXPERIMENTAL INVESTIGATION OF POST-DEPOSITIONAL TAPHONOMIC BIAS IN CONODONTS
Bibliographic record
Abstract
The different types of elements that occurred together in conodont apparatuses are not recovered from the fossil record in the expected numbers. The causes of this are complex and difficult to study. Numerous complete articula- ted skeletons of Ozarkodina excavata (Branson and Mehl) have been recovered from the Eramosa Member at Hep- worth, Ontario, and as a consequence, several of the poten- tial biases affecting recovery of isolated conodont elements can be ruled out a priori. Based on processing ten replicate samples ('runs') of nodular carbonate and bituminous shale, we tested the role of post-mortem compaction, laboratory processing and difficulties in element identification in biasing the expected, or predicted, recovery of apparatus elements. Although the numbers of different elements of O. excavata reported in the literature do not exhibit as marked a bias as do Late Palaeozoic conodont faunas, they are biased nonetheless. This is also true of elements recovered from the Eramosa Member. In both carbonate and shale samples, P1 and S1 ⁄ 2 elements are significantly under-represented, whereas P2 and S0 elements are significantly over-represen- ted. In the carbonate runs, this bias is a consequence of the difficulties in differentiating between broken remains of mor- phologically similar elements. When this factor is taken into account in the shale runs, however, the fauna still exhibits significant bias, and we are able to rule out all potential bia- ses except one. Surprisingly, apparent over-representation of P elements and under-representation of S elements can arise as a result of element fragmentation during sediment com- paction and diagenesis alone.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".