In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].

[EX Q]: El articulo presenta un estudio de la percepcion que tienen los ingenieros de requisitos (noveles y expertos) en relacion a la efectividad de las diferentes tecnicas de educcion para el descubrimiento de los requisitos en un proyecto de desarrollo de software. El articulo trata un tema que merece cierta atencion ante la gran cantidad de tecnicas de educcion que existen y la desorientacion de los ingenieros de requisitos respecto de cual utilizar en un determinado contexto. El estudio realizado considera como noveles Ingenieros que no tienen conocimiento de tecnicas de educcion y uno de los atributos que debe ser calificado como base del estudio comparativo, es precisamente su experiencia. De hecho como conclusion se expresa que "una mas amplia formacion y principalmente de tipo practica, es necesaria para que los ingenieros noveles puedan decidir.", eso es de Perogrullo. Deberia ser considera una gama mayor de atributos del contexto como los sugeridos en [14], que permitan conclusiones mas veraces.
[EX A]: es

[EX Q]: Conclusiones: "... cambiar el paradigma del actual desarrollo de aplicaciones enfocadas en esta area, la pregunta a realizar ya no debe ser Como se realizara el plegado de la proteina?, sino el como se puede mejorar la forma de aplicar las reglas de Meckler. ..." LAS CONCLUSIONES NO SON CLARAS. HAY MUCHO TRABAJO A FUTURO. POR EJEMPLO: "...queda abierta la interrogante acerca de como se puede mejorar la simulacion de tal manera que la secuencia de aminoacidos..." DEBEN REDACTAR LAS CONCLUSIONES BASADAS EN LOS RESULTADOS EXPERIMENTALES Y LA TEORIA USADA.
[EX A]: es

[EX Q]: This paper introduces a maximum total correlation procedure, adds a target and then adds noise perturbations. Technical issues: The move from (1) to (2) is problematic. Yes it is a lower bound, but by igoring H(Z), equation (2) ignores the fact that H(Z) will potentially vary more significantly that H(Z|Y). As a result of removing H(Z), the objective (2) encourages Z that are low entropy as the H(Z) term is ignored, doubly so as low entropy Z results in low entropy Z|Y. Yes the -H(X|Z) mitigates against a complete entropy collapse for H(Z), but it still neglects critical terms. In fact one might wonder if this is the reason that semantic noise addition needs to be done anyway, just to push up the entropy of Z to stop it reducing too much. In (3) arbitrary balancing paramters lamda_1 and lambda_2 are introduced ex-nihilo - they were not there in (2). This is not ever justified. Then in (5), a further choice is made by simply adding L_{NLL} to the objective. But in the supervised case, the targets are known and so turn up in H(Z|Y). Hence now H(Z|Y) should be conditioned on the targets. However instead another objective is added again without justification, and the conditional entropy of Z is left disconnected from the data it is to be conditioned on. One might argue the C(X,Y,Z) simply acts as a prior on the networks (and hence implicitly on the weights) that we consider, which is then combined with a likelihood term, but this case is not made. In fact there is no explicit probabilistic or information theoretic motivation for the chosen objective. Given these issues, it is then not too surprising that some further things need to be done, such as semantic noise addition to actually get things working properly. It may be the form of noise addition is a good idea, but given the troublesome objective being used in the first place, it is very hard to draw conclusions. In summary, substantially better theoretical justification of the chosen model is needed, before any reasonable conclusion on the semantic noise modelling can be made.
[EX A]:
en