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Record W7065455026

El Expediente administrativo por siniestros náuticos

2000· dissertation· es· W7065455026 on OpenAlexfundno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2000
Typedissertation
Languagees
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
FundersInstitute of Musculoskeletal Health and ArthritisWorld Meteorological OrganizationInternational Labour OrganizationUnited Nations
KeywordsWork (physics)Control (management)Identification (biology)Context (archaeology)Measure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

constituye trabajo de Tesis, AUTORIZA su presentación a la Comisión de Tercer Ciclo de la Universidad de La Coruña.Pontevedra,, 2 de noviembre de 2000. AGRADECIMIENTONo puedo comenzar este trabajo sin manifestar mi más rendido agradecimiento a cuantos me han ayudado en la larga travesía que culmina ahora con mi Tesis; en particulaz, mis profesores en esta Escuela, de quienes guazdo.un recuerdo perpetuo de gratitud por tantas horas de labor docente en un clima de compañerismo seguramente único en el sistema universitario, en virtud de la franca disposición de los profesores y del reducido número de alumnos que entonces estudiábamos y vivíamos tantas experiencias personales en esta Institución, tan querida en la ciudad y con una ya dilatada historia.Eran los tiempos en que se iniciaba el nuevo plan de estudios, llevando aparejados diversos cambios en la ordenación administrativa y académica de la Escuela.Eran tiempos de incertidumbre e ilusión que vivimos intensamente profesores y alumnos, algunos, de uno y otro estamento, ya no están fisicamente entre nosotros.Para todos recuerdo, emoción y agradecimiento.

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)0.022
metaresearch head score (Gemma)0.037
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 score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0040.002
Scholarly communication0.0110.006
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0210.006

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 head0.019
GPT teacher head0.278
Teacher spread0.260 · 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
Published2000
Admission routes1
Has abstractno

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