<|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:"Can changes in population mixing and socio-economic deprivation in Cumbria, England explain changes in cancer incidence around Sellafield?."
Abstract:"Previously excesses in incident cases of leukaemia and non-Hodgkin lymphoma have been observed amongst young people born or resident in Seascale, Cumbria. These excesses have not been seen more recently. It is postulated that the former apparent increased risk was related to 'unusual population mixing', which is not present in recent years. This study investigated changes in measures of population mixing from 1951-2001. Comparisons were made between three specified areas. Area-based measures were calculated (migration, commuting, deprivation, population density). All areas have become more affluent, although Seascale was consistently the most affluent. Seascale has become less densely populated, with less migration into the ward and less diversity with respect to migrants' origin. There have been marked changes in patterns of population mixing throughout Cumbria. Lesser population mixing has been observed in Seascale in recent decades. Changes in pattern and nature of population mixing may explain the lack of recent excesses. (C) 2017 Elsevier Ltd. All rights reserved.."
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 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [];
Q3 = [];
Q4 = [0];
Q5 = [1];
Q6 = [1].
Can changes in population mixing and socio-economic deprivation in Cumbria, England explain changes in cancer incidence around Sellafield?
Previously excesses in incident cases of leukaemia and non-Hodgkin lymphoma have been observed amongst young people born or resident in Seascale, Cumbria. These excesses have not been seen more recently. It is postulated that the former apparent increased risk was related to 'unusual population mixing', which is not present in recent years. This study investigated changes in measures of population mixing from 1951-2001. Comparisons were made between three specified areas. Area-based measures were calculated (migration, commuting, deprivation, population density). All areas have become more affluent, although Seascale was consistently the most affluent. Seascale has become less densely populated, with less migration into the ward and less diversity with respect to migrants' origin. There have been marked changes in patterns of population mixing throughout Cumbria. Lesser population mixing has been observed in Seascale in recent decades. Changes in pattern and nature of population mixing may explain the lack of recent excesses. (C) 2017 Elsevier Ltd. All rights reserved.