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Record W2799441972 · doi:10.51291/2377-7478.1323

Sentience, the final frontier....

2018· article· en· W2799441972 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Sentience · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSentienceFish <Actinopterygii>PsychologyZebrafishCognitive scienceCognitive psychologyComputer scienceBiologyArtificial intelligenceFishery

Abstract

fetched live from OpenAlex

Arguments for fish sentience have difficulty with the philosophical zombie problem. Progress in AI has shown that complex learning, pain behavior, and pain as a motivational drive can be emulated by robots without any internal subjective experience. Therefore, demonstrating these abilities in fish does not necessarily demonstrate that fish are sentient. Further evidence for fish sentience may come from optogenetic studies of neural networks in zebrafish. Such studies may show that zebrafish have neural network patterns similar to those that correlate with sentience in humans. Given the present uncertainty regarding sentience in fish, caution should be applied regarding the precautionary principle. Adopting this principle may cause distress to humans, who are certainly sentient, as they strive to protect animals that may not be.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.307
Teacher spread0.286 · 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