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Record W7010759161

Istyald, the Tree of Knowledge : The Kingdom of Istyald

2020· other· en· W7010759161 on OpenAlexaboutno aff

Bibliographic record

VenueGallica (Bibliothèque nationale de France) · 2020
Typeother
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsFantasyKingdomMythologyWhite (mutation)Face (sociological concept)Tree (set theory)Quarter (Canadian coin)Evergreen
DOInot available

Abstract

fetched live from OpenAlex

Apart from a few mythological occurrences, most trees generally do not have proper names in the Middle Ages. At most, they are associated with famous people. It was with the development of the idea that nature should be preserved in the face of rampant industrialization that people in the West began to name trees, particularly in American national parks, and later in fantasy worlds. Tolkien thus gives a name to the oldest of the white trees, as well as to the large trees of Valinor, Telperion and Laurelin. In a similar vein, we can also mention the Ellcrys of the Shannara universe created by Terry Brooks. Remarkably, some large trees in the American National Parks have been given names taken from fantasy universes, such as the Sequoia evergreen Iluvatar, a name inspired by The Silmarillion .

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.300
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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 teacher head, not a consensus.

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
Published2020
Admission routes1
Has abstractyes

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