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Record W7048261091

La evolución del MOCAP en el cine de James Cameron: El arte de la captación de movimiento.

2024· article· es· W7048261091 on OpenAlexaboutno aff

Bibliographic record

VenueZaguan (University of Zaragoza Repository) · 2024
Typearticle
Languagees
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)AvatarMotion (physics)CulminationObject (grammar)
DOInot available

Abstract

fetched live from OpenAlex

La temática de este trabajo de fin de grado es el análisis de la evolución del motion capture a lo largo de la producción cinematográfica del director y guionista canadiense, James Cameron. Se presentarán sus aportaciones más valiosas a la industria a través de algunas de sus producciones más significativas, haciendo especial hincapié en las dos entregas de la franquicia Avatar y como estas representan el culmen de todos los estudios y experimentos realizados durante toda la trayectoria del director.<br />The aim of this work is analysing the evolution of motion capture throughout the film production of the Canadian director and screenwriter James Cameron. It will also present his most valuable contributions to the industry through some of his most significant productions, with special emphasis on the two instalments of the Avatar franchise and how these represent the culmination of all the studies and experiments carried out throughout the director's career.<br /><br />

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.221
Teacher spread0.218 · 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 designBench or experimental
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

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