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Record W4323789542 · doi:10.33137/ic.v30i.39481

Peace Lilies and Words That Heal

2022· article· en· W4323789542 on OpenAlexvenueno aff
Maria Luisa Ierfino-Adornato

Bibliographic record

VenueItalian Canadiana · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicIndian History and Philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyArt

Abstract

fetched live from OpenAlex

The fragrant peace lily has powerful and cathartic vibrations.It protects and heals the soul as it helps transcend reality.The beautiful flower represents the creative act of writing for me.Yes it does wither in the winter, but it is reborn every spring.The peace lily, like every word I humbly use, is pure, therapeutic and energizing.I don't remember a time when I didn't love books or reading, just like I don't remember a time that I didn't exist.I loved writing and it was part of my DNA.Until I decided to be a writer at the irreverent age of sixteen, I wrote from instinct, I wrote for leisure.I gradually became more and more conscious of what propelled me to write.I was able to express my feelings eloquently and freely when I wrote them down.Each day I would write to salute the sun, to whisper to the moon

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)0.003
metaresearch head score (Gemma)0.007
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 score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0160.031
Scholarly communication0.0140.008
Open science0.0010.007
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0260.011

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 head0.034
GPT teacher head0.181
Teacher spread0.148 · 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
Published2022
Admission routes1
Has abstractyes

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