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Record W4225306382 · doi:10.3390/neurosci3020018

The Case for Octopus Consciousness: Temporality

2022· review· en· W4225306382 on OpenAlexaff
Jennifer A. Mather

Bibliographic record

VenueNeuroSci · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicCephalopods and Marine Biology
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsTemporalityoctopus (software)SentienceConsciousnessCuttlefishAssociative learningCognitive psychologyCognitive scienceArtificial intelligenceComputer sciencePsychologyFisheryBiologyEpistemology

Abstract

fetched live from OpenAlex

Temporality is one of the criteria that Birch has advanced for areas of cognitive ability that may underlie animal sentience. An ability to integrate and use information across time must be more than simply learning pieces of information and retrieving them. This paper looks at such wider use of information by octopuses across time. It evaluates accumulation of information about one's place in space, as used across immediate egocentric localization by cuttlefish and medium distance navigation in octopuses. Information about useful items in the environment can be incorporated for future use by octopuses, including for shelter in antipredator situations. Finding prey is not random but can be predicted by environmental cues, especially by cuttlefish about future contingencies. Finally, the paper examines unlimited associative learning and constraints on learning, and the ability of cephalopods to explore and seek out information, even by play, for future use.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.115
GPT teacher head0.331
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

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".

Quick stats

Citations43
Published2022
Admission routes1
Has abstractyes

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