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Record W7068715287

Revista IDIS

2017· other· es· W7068715287 on OpenAlexaboutno aff

Bibliographic record

VenueRepositorio Institucional (Universidad de Cuenca) · 2017
Typeother
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansPersonaPopulationContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

En Cuenca, del 17 al 22 de abril de 1978 se llevó a cabo el Segundo Encuentro de Historia y Rea1idad Económica y Social del Ecuador. Este encuentro corrió a cargo del Instituto de Investigaciones Sociales de la Universidad de Cuenca y estuvo patrocinado por esa Universidad, la Central de Quito, la Sede en Cuenca de la Pontificia Universidad Católica del Ecuador, la Sede en Quito de la Facultad Latinoamericana de Ciencias Sociales (FLACSO), la Sede en Quito del Instituto Latinoamericano de Investigaciones Sociales (ILDIS), la Casa de la Cultura Ecuatoriana, Núcleo del Azuay; el Centro de Investigaciones Económicas y Sociales del Ecuador (CIESE), la Universidad de York, Toronto, Canadá; y el Banco Central del Ecuador. \nEl Primer Encuentro se habla reunido también en Cuenca y, en vista de sus buenos resultados, se designó, nuevamente, al Instituto de Investigaciones Sociales de la Universidad de Cuenca organizador y sede del Segundo Encuentro. Al término de éste, y, por las mismas razones, se encargó al mismo Instituto la organización del Tercer Encuentro, programado para dentro de dos años aproximadamente. \nLa tónica de este Intenso seminario fue de seriedad. No hubo ni repetición de ciertos datos estadísticos, ni descripciones 1nút1les por sabidas y yeyunas de análisis de una alegre fenomenología de la realidad nacional, ni de denuncias apasionadas,ni manipulación política de la Investigación.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.316
Threshold uncertainty score0.975

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0080.002
Scholarly communication0.0080.006
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3160.129

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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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.

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
Published2017
Admission routes1
Has abstractyes

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