Bibliographic record
Abstract
Potential competing interests: No potential competing interests to declare.I rather enjoyed reading this paper.It suffers, however, from a large number of typographic and minor grammatical errors and deserves a thorough editing.That aside, this is an interesting approach.The mathematician in me enjoyed the linkage between symplectic geometry and the Scrodinger formulation.It motivates an origin for that equation, which otherwise appears rather ad hoc.I was not sure how the overlaps were actually calculated.Are they going to be based on the wave functions of the Schrodinger formulation, or on bra-ket calculations.Eigenstates are often defined over the entire of the space, as may be momentum distributions, so if the overlap were simply domain based, most everything would have significant overlap.If these are based on bra-ket integrals then this would not be at issue because one would be viewing them within the Hilbert space and measuring degrees of orthogonality.The later definitions seem to suggest the latter while the pictures suggest the former.
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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.025 |
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".