Bibliographic record
Abstract
At the time of writing, the CoViD-19 pandemic was in its second wave with infections doubling every several days to two weeks in many parts of the world. Such geometric (or exponential) expansion is the hallmark of unconstrained population growth in all species ranging from submicroscopic viral particles through bacteria to whales and humans; this suggests a kind of ‘fractal geometry’ in bio-reproductive patterns. In nature, population outbreaks are invariably reversed by the onset of both endogenous and exogenous negative feedback – reduced fecundity, resource shortages, spatial competition, disease, etc., serve to restore the reference population to below carrying capacity, sometimes by dramatic collapse. H. sapiens is no exception – our species is nearing the peak of a fossil-fueled ~200 year plague-like population outbreak that is beginning to trigger serious manifestations of negative feedback, including climate change and CoViD-19 itself. The human population will decline dramatically; theoretically, we can choose between a chaotic collapse imposed by nature or international cooperation to plan a managed, equitable contraction of the human enterprise.
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".