Identificación de las variables que intervienen en la percepción del consumidor de productos remanufacturados
Bibliographic record
Abstract
En las ultimas decadas diversos paises como Estados Unidos,Canada, Mexico, Brasil, Alemania, Rusia, Japon, China yotros que se mencionan posteriormente, han continuadodesarrollandose en los sectores politicos, economicos,sociales y culturales. En este contexto las naciones tienencomo fin la busqueda del bienestar comun, la seguridad, lacompetitividad tecnologica, comercial y el desarrollosustentable. Actualmente vivimos en un mundo globalizadocon tendencias del tipo capitalista, donde se busca generarriqueza a traves de la transformacion de recursos, los cualesen su mayoria son finitos o solo renovables bajo ciertascondiciones, debido a esta problematica se han disenadootras alternativas de produccion tales como la remanufactura,donde se busca extender el ciclo de vida de los productos atraves de procesos de recuperacion, limpieza,reacondicionamiento e instalacion de componentes clavepara cumplir con la produccion necesaria para satisfacer lasnecesidades de la poblacion. Este tipo de practicas son mascomunes en paises desarrollados tales como Noruega,Australia, Suiza, Paises Bajos, Estados Unidos, Alemania,Nueva Zelanda, Canada, Singapur y Dinamarca dondeexisten los incentivos, tecnologias, conocimiento ydisposiciones apropiadas formando un contraste con lospaises emergentes como son Rusia, China, India, Mexico yBrasil donde las capacidades no estan del todo desarrolladas.En este articulo se pretende identificar cuales son lasvariables que intervienen en la percepcion del consumidor deproductos remanufacturados con el fin de comprender losimpedimentos o diferencias generadas para lograr adoptar unmodelo economico circular basado en operaciones deremanufactura.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".