Bibliographic record
Abstract
‘The marvellous thing about the face of the earth is that it is such a mess.’ Richard Fortey (2004: 432) makes this remark near the end of his ‘intimate history’ of the earth. Messiness is not a description that would have occurred in the 1790s to Hutton. He had sensed order, harmony, and a ‘beautiful economy’ in the physical world. Fortey, though, is not using the word ‘mess’ in a derogatory sense. Nor is he denying that there is order in the systems geology describes. He is thinking of things that, as an eminent geologist, he knows and loves best: rocks. Many different geological and biological processes in many different time periods have left marks on particular locales. Understanding these presents daunting challenges. Messiness activates ordering impulses. It led to the familiar typecasting of rocks as igneous, metamorphosed, or sedimentary (and to the categorization of geologists as ingenious, metaphoric, or sedentary [Anderson, 2007: 189]). It stimulates the much more complicated task of ordering earth-history events such as glaciation, the movement and shifting alignments of plates, the evolutionary links among species over time and the extinctions of these, and atmospheric change.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.007 |
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".