Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Functions in functional languages have a single elimination form — application — and cannot be compared, hashed, or subjected to other non-application operations. These operations can be approximated via defunctionalization: functions are replaced with first-order data and calls are replaced with invocations of a dispatch function. Operations such as comparison may then be implemented for these first-order data to approximate e.g. deduplication of continuations in algorithms such as unbounded searches. Unfortunately, this encoding is tedious, imposes a maintenance burden, and obfuscates the affected code. We introduce an alternative in intensional functions , a language feature which supports the definition of non-application operations in terms of a function’s definition site and closure-captured values. First-order data operations may be defined on intensional functions without burdensome code transformation. We give an operational semantics and type system and prove their formal properties. We further define intensional monads , whose Kleisli arrows are intensional functions, enabling monadic values to be similarly subjected to additional operations.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 it