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Record W2408911392

Illness and metaphor: Hay fever

2003· article· en· W2408911392 on OpenAlexvenueno aff
A. A. Milne

Bibliographic record

VenueCanadian Medical Association Journal · 2003
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsHay feverMedicineGermanAsideHayReading (process)MetaphorClassicsLiteraturePhilosophyTheologyHistoryArtLinguistics
DOInot available

Abstract

fetched live from OpenAlex

“Try this. The chemist says it's the best hay-fever cure there is.” “It's in a lot of languages,” I said as I took the wrapper off. “I suppose German hay is the same as any other sort of hay? Oh, here it is in English. I say this is a what-d'-you-call-it cure.” “So the man said.” “Homœopathic. It's made from the pollen that causes hay-fever. Yes. Ah, yes.” I coughed, slightly, and looked at Beatrice out of the corner of my eye. “I suppose,” I said, carelessly, “if anybody took this who hadn't got hay-fever, the results might be rather — I mean that he might then find that he — in fact, er — had got it.” “Sure to,” said Beatrice. “Yes. That makes us a little thoughtful; we don't want to over-do this thing.” I went on reading the instructions. “You know, it's rather odd about my hay-fever — it's generally worse in town than in the country.” “But then you started so late, dear. You haven't really got into the swing of it yet.” “Yes, but still — you know, I have my doubts about the gentleman who invented this. We don't see eye to eye in this matter, Beatrice, you may be right — perhaps I haven't got hay-fever.” “Oh, don't give up.” “But all the same I know I've got something. It's a funny thing about my being worse in town than in the country. That looks rather as if — By Jove, I know what it is — I've got just the opposite of hay-fever.” “What is the opposite of hay?” “Why, bricks and things.” I gave a last sneeze and began to wrap up the cure. “Take this pollen stuff back,” I said to Beatrice, “and ask the man if he's got anything homœopathic made from paving-stones. Because, you know, that's what I really want.” “You have got a cold,” said Beatrice. From A.A. Milne, “A Summer Cold.” In: The Holiday Round, London: Methuen; 1912.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.020
Scholarly communication0.0050.009
Open science0.0010.004
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0100.002

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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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