Video playback demonstrates episodic personality in the gloomy octopus
Bibliographic record
Abstract
Coleoid cephalopods, including octopuses, cuttlefish and squid, rely mainly on visual signals when interacting with conspecifics, predators and prey. Presenting visual stimuli, such as models, photographs, mirrors and live conspecifics, can thus provide insight into cephalopod behaviour. These methods, however, have limitations - mirrors and live animals lack experimental control, whereas models and photographs sacrifice motion-based information. Video playback addresses these issues by presenting controlled, moving and realistic stimuli but, to date, video playback has not been used successfully with any cephalopod. Here, we developed a video playback technique for the gloomy octopus (Octopus tetricus) that incorporated recent advances in video technology. We then used this technique to test for personality, which we defined as behavioural differences between individuals that are consistent over time and across ecologically important contexts. We captured wild octopuses and tested them on 3 separate days over a 10 day period. On each test day, subjects were presented with videos of a food item, a novel object and a conspecific. These represented a foraging, novel and threatening context, respectively. A fourth video without a moving stimulus controlled for the playback monitor itself and potential artifacts associated with video playback. Experimental stimuli evoked unambiguous and biologically appropriate responses from the subjects. Furthermore, individuals' responses to the three experimental contexts were highly correlated within a given test day. However, within a given context, individuals behaved inconsistently across the 3 test days. The reordering of ranks suggests that rather than fulfilling the criteria for personality, gloomy octopus show temporal discontinuities, and hence display episodic personality.
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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 | 0.000 |
| 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) | 0.001 | 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".