MétaCan
Menu
← Back to cohort
Record W7099231498

COMMENT Food of the dogs

2013· article· en· W7099231498 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsMinkReading (process)Subject (documents)The ImaginaryColumn (typography)Subject matter
DOInot available

Abstract

fetched live from OpenAlex

Once again, while Greg is slacking off on vacation, his two dogs, Mink and Clifford, nobly pitch in to keep his column going. For those of you who have not met them previously (they are semi-regulars to these pages), Mink is a brave, loyal, intelligent chocolate Labrador retriever whose duties include guarding the house and watching over the family by testing all food to make sure it’s safe to eat. Clifford, a small mixed poodle/spaniel, seems primarily to have the job of chasing tennis balls. As usual, their column takes the form of an imaginary dialog, much like those invented by Plato between Socrates and Glaucon. Of course, it’s also possible that Plato borrowed the literary device from Mink and Clifford. Classical scholars are still debating this point. Editor Mink (reading aloud): “It was the best of times, it was the worst of times.” Clifford: Well, which was it? Mink (ignoring him): “It was the age of wisdom, it was the age of foolishness.” Clifford: For Pete’s sake, make up your mind! Mink (sighing): I’m just reading you the opening of Charles Dickens’s novel A Tale of Two Cities. Clifford: It seems to me this guy Dickens really likes to cover his-Mink (quickly): Never mind. Greg suggested I might start with that quotation because he thinks the subject of our column this month is one more piece of evidence that we are living in the age of foolishness. I want to discuss the matter of Paleofood. Clifford (who wasn’t paying much attention until hearing the word “food”): Pail of food? I’d love a pail of food! What kind of food is in it? Mink: Not pail of food, Paleofood. It’s an increasingly popular food movement. Clifford: If the food is still moving, we can just jump on it and-

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.002
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0870.017

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 head0.190
Teacher spread0.170 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicCulinary Culture and Tourism→French-language works237,207→