Bibliographic record
Abstract
Multiples? What multiples? This was the reply to my questioning of the seismic-to-synthetic log mis-tie shown in Figure 1. My inquiry followed a request for technical assistance in an AVO inversion project by a young entry-level geophysicist interpreting the thin tram-track reservoirs typical of the Western Canadian Sedimentary Basin (WCSB). The project had been initiated with this log tie to establish the spectral characteristics of a wavelet needed for inversion and despite being at the end of the AVO-compliant processing flow, I suggested that we take a step back to deal with the obvious multiple contamination clearly visible within the zone of interest. I was met with blank stares, as there had been no discussion about multiples. It even crossed my mind that maybe multiples had not been a part of my young colleague's education and training. If this was indeed the case, then it was not her oversight, as I had seen no new technology or even convention presentations trying to address this persistently insidious land internal-multiple problem since the last time I was fully engaged in the mid 1990s.
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 | 0.000 | 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) | 0.006 | 0.004 |
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; both teacher heads agree on what is shown here.
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".