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ILCR. International Law Clinic Reports. Informes de la Clínica Jurídica Internacional. Vol. 4

2023· report· es· W4377825944 on OpenAlexfundno aff
Héctor Olásolo, Robert-Joseph-Blaise MacLean, Luisa Villarraga Zschommler, Sofía Linares Botero, Federico Freydell, Anggie Paola Abril Rincón, Valentina Bocanegra Oyola, María Juliana Bonilla Tovar, Sol Cristina Bustamante Chávez, Daniel Camilo Guerrero Gutiérrez, Laura Daniela Guzmán Salinas, Andrea Jimena Hurtado Fonseca, Dayanna Margot Petronilla Cruz Quispe, Laura Tobón Vélez, Daniela Velásquez Aponte, Olga Herrera Carbuccia

Bibliographic record

Venuenot available
Typereport
Languagees
FieldMedicine
TopicEthics and bioethics in healthcare
Canadian institutionsnot available
FundersChangchun Institute of Applied ChemistryCentre for Engineering Research and DevelopmentEnvironment and Climate Change Canada
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

El cuarto volumen de la colección International Law Clinic Reports (ILCR) / Informes de la Clínica Jurídica Internacional (ICJI) aborda cuestiones jurídicas relacionadas con el sistema de reparaciones de la Corte Penal Internacional, en esta ocasión se analiza la cuestión jurídica del daño transgeneracional. El daño transgeneracional fue identificado en los descendientes de los sobrevivientes del Holocausto y ha sido objeto de numerosos estudios e investigaciones. Los crímenes graves previstos en el Estatuto como la violación, los abusos sexuales, el genocidio, las masacres, entre otros, pueden afectar generaciones futuras provocando consecuencias traumatizantes en los descendientes que podrían dar lugar a reparación.

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)0.010
metaresearch head score (Gemma)0.032
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: Other · Consensus signal: Other
Teacher disagreement score0.185
Threshold uncertainty score0.618

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.013
Science and technology studies0.0030.002
Scholarly communication0.0080.004
Open science0.0030.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.1850.098

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 head0.200
GPT teacher head0.510
Teacher spread0.310 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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