An electrophysiological investigation of referential communication
Bibliographic record
Abstract
A key aspect of linguistic communication involves semantic reference to objects. Presently, we investigate neural responses at objects when reference is disrupted, e.g., "The connoisseur tasted *that wine"… vs. "…*that roof…" Without any previous linguistic context or visual gesture, use of the demonstrative determiner "that" renders interpretation at the noun as incoherent. This incoherence is not based on knowledge of how the world plausibly works but instead is based on grammatical rules of reference. Whereas Event-Related Potential (ERP) responses to sentences such as "The connoisseur tasted the wine …" vs. "the roof" would result in an N400 effect, it is unclear what to expect for doubly incoherent "…*that roof…". Results revealed an N400 effect, as expected, preceded by a P200 component (instead of predicted P600 effect). These independent ERP components at the doubly violated condition support the notion that semantic interpretation can be partitioned into grammatical vs. contextual constructs.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".