Bibliographic record
Abstract
At what time does the afternoon start, at 1 p.m. or 3 p.m.? Language understanding requires the ability to correctly match statements to their real-world meaning. This mapping process is a function of the context, which includes various factors such as location and time as well as the speaker’s and listeners’ backgrounds. For example, an utterance like, “It is hot today,” would mean different things were it expressed in Death Valley versus Alaska. Based on our background and experiences, people have different interpretations for time expressions, color descriptions, geographic expressions, qualities, relative expressions, and more. This ability to map language to real-world meaning is also required from the language technology tools we use. For example, translating a recipe that contains instructions to “preheat the oven to 180 degrees” requires a translation system to understand the implicit scale (e.g. Celsius versus Fahrenheit) based on the source language and the user’s location. To date, no automatic translation systems can do this, and there is little “grounding” in any widely used language technology tool.
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 | 0.000 | 0.000 |
| 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".