<|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:"Evolution Characteristics of Spatial Concentration Patterns of Interprovincial Population Migration in China from 1985 to 2015."
Abstract:"People migrate between places constantly, promoting population redistribution and socioeconomic element flows. Since China's interprovincial population migration flows are highly concentrated in particular places and there are comparatively few studies using a spatial concentration perspective in this field, there is room for a spatial analysis. The Gini Index (GI) is commonly used in analysing the concentration of topological data, and it works well with migration flow data. Also, GI is scale-invariant due to its normalized nature, and hence it is readily interpretable. However, due to missing data, the traditional GI specification is often an underestimate. Thus, the authors propose the GIc for better standardisation, and demonstrate its utility in the characterization of interprovincial migration flows in China from 1985 to 2015, quantifying the spatial concentration of migration. The results indicate that (a) the GIc measures the concentration degree of population migration better; (b) collectively, the concentration is consistently high, and it shows a trend in an inverse U-shape over six periods, and there are strong linkages between regions with high origin GIcs and regions with high destination GIcs; (c) since 1995, the concentration at migration origins is high in middle China and some western regions; migration destinations with high concentration are the Yangtze River Delta and the Pearl River Delta, which show a smooth temporal change; (d) origins with high concentration are often connected to destinations with high concentration by strong migration flows that move large populations.."
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].
Evolution Characteristics of Spatial Concentration Patterns of Interprovincial Population Migration in China from 1985 to 2015
People migrate between places constantly, promoting population redistribution and socioeconomic element flows. Since China's interprovincial population migration flows are highly concentrated in particular places and there are comparatively few studies using a spatial concentration perspective in this field, there is room for a spatial analysis. The Gini Index (GI) is commonly used in analysing the concentration of topological data, and it works well with migration flow data. Also, GI is scale-invariant due to its normalized nature, and hence it is readily interpretable. However, due to missing data, the traditional GI specification is often an underestimate. Thus, the authors propose the GIc for better standardisation, and demonstrate its utility in the characterization of interprovincial migration flows in China from 1985 to 2015, quantifying the spatial concentration of migration. The results indicate that (a) the GIc measures the concentration degree of population migration better; (b) collectively, the concentration is consistently high, and it shows a trend in an inverse U-shape over six periods, and there are strong linkages between regions with high origin GIcs and regions with high destination GIcs; (c) since 1995, the concentration at migration origins is high in middle China and some western regions; migration destinations with high concentration are the Yangtze River Delta and the Pearl River Delta, which show a smooth temporal change; (d) origins with high concentration are often connected to destinations with high concentration by strong migration flows that move large populations.