Bibliographic record
Abstract
The paper is in essence a survey of categories having φ-weighted colimits for all the weights φ in some class Φ.We introduce the class Φ + of Φ-flat weights which are those ψ for which ψ-colimits commute in the base V with limits having weights in Φ; and the class Φ -of Φ-atomic weights, which are those ψ for which ψ-limits commute in the base V with colimits having weights in Φ.We show that both these classes are saturated (that is, what was called closed in the terminology of [AK88]).We prove that for the class P of all weights, the classes P + and P -both coincide with the class Q of absolute weights.For any class Φ and any category A, we have the free Φ-cocompletion Φ(A) of A; and we recognize Q(A) as the Cauchy-completion of A. We study the equivalence between (Q(A op ))op and Q(A), which we exhibit as the restriction of the Isbell adjunction between [A, V] op and [A op , V] when A is small; and we give a new Morita theorem for any class Φ containing Q.We end with the study of Φ-continuous weights and their relation to the Φ-flat weights.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".