Bibliographic record
Abstract
Back in the mid-1960s, I was a feral sort of a child who loved scampering around construc-tion sites, climbing the huge, grey piles of excavated shale that were popping up all over my rapidly developing Toronto suburb. I might have been six or so when I first really noticed the slabs of muddy smelling rock often contained the imprints of scallop shells, snails, and fragments of coral, things I recognized from picture books but hadn’t yet seen in real life as we lived hundreds of miles from the near-est ocean. Yet 450 million years before, during the Ordovician era, where I was playing would have been the middle of a vast ocean whose limpid, tropical waters teemed with fantastic life forms such as giant, predatory sea scorpions and nautiloids that jetted through the primeval currents like living missiles. I knew this from visiting the Royal Ontario Museum’s brand new, McLuhan-inspired, Hall of Invertebrate Paleontology, which recreated detailed dioramas of life in Ontario’s ancient seas, complete with theatrical lighting and interactive, taped-looped narratives played through banks of telephone receivers
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.010 |
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".