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
Sequences are indicative of signal complexity in vocal communication. While vocal sequences are well-described in birds and terrestrial mammals, the extent to which marine mammals use them is less well understood. This study documents the first known examples of sequence use in the narwhal (Monodon monoceros), a gregarious Arctic cetacean. Eight female narwhals were fitted with animal-borne recording devices, resulting in one of the largest datasets of narwhal acoustic behaviour to date. A combination of visual and quantitative classification procedures was used to test whether subjectively defined vocalization patterns were organized into sequences. Next, acoustic characteristics were analyzed to assess whether sequences could disclose group or individual identity. Finally, generalized linear models were used to investigate the behavioural context under which sequences were produced. Two types of sequences, consisting of “paired” patterns and “burst pulse series,” were identified. Sequences of burst pulse series were typically produced in periods of high vocal activity, whereas the opposite was true for sequences of paired patterns, suggesting different functions for each. These findings extend the set of odontocetes which are known to use vocal sequences. Inquiry into vocal sequences in other understudied marine mammals may provide further insights into the evolution of vocal communication.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.014 |
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