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Record W4309603145 · doi:10.3390/neurosci3040047

The Case for Octopus Consciousness: Valence

2022· review· en· W4309603145 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
KeywordsValence (chemistry)Consciousnessoctopus (software)PerceptionPsychologyCognitive psychologyGeneralist and specialist speciesCognitive scienceEcologyBiologyNeurosciencePhysics

Abstract

fetched live from OpenAlex

Octopuses may demonstrate perceptual richness, neural unity, temporality, and finally, valence or affective evaluation, as the neural basis for consciousness. Octopuses attach a positive valence to food as 'specializing generalists' with long-term learning and flexible choices. They value shelter, yet modify, adapt and even transport it where necessary. They attach a negative valence to what may be described as pain, monitoring and protecting the damaged area and learning to associate locations with pain relief. Finally and surprisingly, octopuses attach a negative value to uncertainty so that they explore their environment before exploiting certain aspects of it and even exhibit motor play. This series of four papers, culminating in the present one, demonstrates in detail why the Cambridge Declaration of Consciousness has suggested octopuses might have the substrate for consciousness, although it is likely not similar to or as complex as that shown by 'higher' vertebrate lineages.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0000.001
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 head0.089
GPT teacher head0.315
Teacher spread0.226 · 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

Citations41
Published2022
Admission routes1
Has abstractyes

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