<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"Mapping of functional areas in Spain based on mobile phone data during different phases of the COVID-19 pandemic."
Abstract:"Mobility functional areas are tools based on human mobility that can be useful for spatial and transport planning in delicate situations such as the COVID-19 pandemic. In this work, we aim to map functional areas in Spain from four days corresponding to different phases of the disease. For that goal, mobile phone data provided by Spanish Statistical National Institute (INE) has been used due to its value and potential to provide constantly updated information of mobility at almost-real time. The methodology consists of a network analysis over an origin-destination matrix to obtain modularity values for 3214 population cells provided by the INE. These values were then used to cluster the cells into functional areas. The results show how different confinement and mobility restriction policies influence the amount, size and shape of the functional areas, and therefore, they affect access to services or jobs.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
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Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
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Q6 = [1].
Mapping of functional areas in Spain based on mobile phone data during different phases of the COVID-19 pandemic
Mobility functional areas are tools based on human mobility that can be useful for spatial and transport planning in delicate situations such as the COVID-19 pandemic. In this work, we aim to map functional areas in Spain from four days corresponding to different phases of the disease. For that goal, mobile phone data provided by Spanish Statistical National Institute (INE) has been used due to its value and potential to provide constantly updated information of mobility at almost-real time. The methodology consists of a network analysis over an origin-destination matrix to obtain modularity values for 3214 population cells provided by the INE. These values were then used to cluster the cells into functional areas. The results show how different confinement and mobility restriction policies influence the amount, size and shape of the functional areas, and therefore, they affect access to services or jobs.