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Record W2196332838 · doi:10.51291/2377-7478.1055

Why is fish “feeling” pain controversial?

2016· article· en· W2196332838 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 · 2016
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsJargonSentienceConsciousnessArgument (complex analysis)FeelingPhilosophy of mindCertaintyPsychologyKey (lock)Fish <Actinopterygii>EpistemologyCognitive sciencePhilosophyMedicineSocial psychologyMetaphysicsComputer scienceLinguistics

Abstract

fetched live from OpenAlex

In his excellent target article, Key (2016) develops a mechanistic argument in an attempt to show why it is unlikely that fish can “feel” pain or for that matter, “feel” anything. The topic is controversial and likely to achieve the goal of getting many hits for the inaugural issue of the new journal, Animal Sentience. In my view, the question is unlikely to be answered, for two reasons. First, because the proponents of the “fish feel pain” controversy are untrained and unskilled in the details and jargon of neurophysiology and/or neuroanatomy, and the opponents of the controversy, like Key, are untrained and unskilled in the details and jargon regarding the philosophy of consciousness. Second, the neural substrate of consciousness in any animal, including humans, has not been clearly delineated with absolute certainty.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.254
Teacher spread0.162 · 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