MétaCan
Menu
Back to cohort
Record W7065782823

Elementul superlativ bdquo;Cel mairdquo; în romanul bdquo;Cel mai iubit dintre pământenirdquo; de Marin Preda

2024· article· ro· W7065782823 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languagero
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsPrecision Nanosystems (Canada)
Fundersnot available
KeywordsField (mathematics)Data collectionPerspective (graphical)Work (physics)Context (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Rezumat: De cele mai multe ori, romanul "Cel mai iubit dintre pământeni" de Marin Preda s-a cercetat doar în plan literar, la nivel de strategii literare utilizate, a conținutului, subiectului și planurilor narative, individualitatea personajelor create de autor, dar mai puțin s-a atras atenția asupra anumitor particularități lingvistice ale stilului de scriere al autorului.Astfel, în acest articol ne-am propus să cercetăm, în plan statistic și interpretativ, ocurențele și valoarea elementului superlativ "cel mai" din construcția superlativului relativ, care apare în chiar titlul romanului.

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)0.009
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: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.007
Scholarly communication0.0070.006
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0340.008

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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicRadiation Therapy and DosimetryFrench-language works237,207