cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3859854.v1
title: Analysis of insect behavior between two different habitats: Grassland and Woodlot

description: <b>Variables</b> Habit: Represented by two letters “W” and “G”, “W” will represent woodlot and “G” grassland. Bowl Color: Bowl color used throughout the experiment. “W” , “Y”, “B” represent white, yellow, and blue respectively. # Insects: Represent the number of insects present in sample collected. # Species: Represents the amount of different species observed. <b>Hypothesis</b> The sample size of the insects collected in the woodlot should be greater in comparison to the grassland. This is because the woodlot is more diverse in comparison to the grassland in terms of plant of species. Next, the white bowl color will stand out more and thus possibly attract more insects than the rest of bowl colors. <b>Methods</b> The weather condition was not ideal for conducting the experiment, there was light rain and significant cloud cover, the temperature was 15 Celsius. The group partners that assisted in conducting the experiment were Numra, and Candice. In order to conduct this experiment 10 solo bowls were placed a meter apart from each other in a random location in each habitat. Next, poured soapy water in all of the bowls and set the timer for an hour. A flashlight was used to assist in conducting an accurate account of the insects collected in the solo bowls, due to the poor weather conditions.
DOI: 10.7910/dvn/v1rjpf/5xdrwl
title: snk20170704_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/byevm9
title: snk20170910_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859848
title: Frequency of insects in grasslands collected using sweep nets and transects

description: Metadata:# of insects refers to the number of different insects found in each replicate. # of RTUs refers to the number of unique recognizable taxonomic units. The replicates are each time we did the procedure. The procedure The length of the transect was 17 meters and each collection using the sweep net procedure was 25 seconds long. The collector would walk along the transect randomly placed in the grass land and continuously sweep the net until they got to the end of the transect then record the data. The procedure was repeated 10 times. <br>Description:the hypothesis: The inclement weather will negatively affect the number of bugs found and collected. <br>the data collection took place on a York University grassland on September 26th at 3:00 pm until approximately 4:00 pm on a rainy cloudy day. the purpose of this experiment was to get familiarized with sampling tools. the tools used where a sweep net and a transect. the data was collected by using the sweep net and walking along a transect. By looking at the data one can tell that the weather did in fact seem to have a negative on the number of bus present.
DOI: 10.7910/dvn/v1rjpf/x4lpgc
title: snk20171126_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/gw2efh
title: snk20170712_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859842
title: Estimating insect abundance using distance based techniques

description: Variables: <br>1) Insect amount in GL: Using a quadrant, random areas of the Grassland were measured for insect amount<br>2)Types of insects in GL: Using a quadrant, random areas of the grassland were measured for types of insects<br>3) Insect amount in WL: Using a quadrant, random areas of the Woodlot were measure for insect amount<br>4)Types of insects in WL: Using a quadrant, random areas of the woodlot were measured for types on insects<br>Description: <br>An ecology lab was held on September 26th, 2016 between 2:30-5:30 at York university held by TA Bailey hewitt. The objective of the lab was to estimate insect abundance within the quadrants randomly placed around the grassland and the woodlot. The focus was on the amount and types of insects found within the vegetation in the quadrant. The weather conditions were rainy, wet, and muggy at 19 degrees celsius. 10 quadrant measurments were done in the grassland, and another 10 quadrant measurements were done in the woodlot. <br>Hypothesis/Prediction:<br>According to the weather conditions, more insects should be naturally found in the woodlot because of the extra protection from the rain. Whereas in the grassland insects can be found but not as easily, since they are straying away from the wet rain. The hypothesis was proven to be true as there was more variety of insects and a higher amount of insects.
DOI: 10.7910/dvn/v1rjpf/vgtsb0
title: snk20170106_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859842.v1
title: Estimating insect abundance using distance based techniques

description: Variables: <br>1) Insect amount in GL: Using a quadrant, random areas of the Grassland were measured for insect amount<br>2)Types of insects in GL: Using a quadrant, random areas of the grassland were measured for types of insects<br>3) Insect amount in WL: Using a quadrant, random areas of the Woodlot were measure for insect amount<br>4)Types of insects in WL: Using a quadrant, random areas of the woodlot were measured for types on insects<br>Description: <br>An ecology lab was held on September 26th, 2016 between 2:30-5:30 at York university held by TA Bailey hewitt. The objective of the lab was to estimate insect abundance within the quadrants randomly placed around the grassland and the woodlot. The focus was on the amount and types of insects found within the vegetation in the quadrant. The weather conditions were rainy, wet, and muggy at 19 degrees celsius. 10 quadrant measurments were done in the grassland, and another 10 quadrant measurements were done in the woodlot. <br>Hypothesis/Prediction:<br>According to the weather conditions, more insects should be naturally found in the woodlot because of the extra protection from the rain. Whereas in the grassland insects can be found but not as easily, since they are straying away from the wet rain. The hypothesis was proven to be true as there was more variety of insects and a higher amount of insects.
DOI: 10.7910/dvn/v1rjpf/7aqdnw
title: snk20171016_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/mgnhxs
title: snk20170828_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/u6vjsl
title: snk20170327_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/vhvzbp
title: snk20171206_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/amnmec
title: snk20171207_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/tqmmp9
title: snk20171213_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/unsncj
title: snk20170724_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859818
title: BIOL 2050 WK4 STEP 2 DATA

description: VARIABLES<br>LOCATION: Saywell Woods, York University, ONSITE TYPE: The type of ecosystem in which data was collected. Categorical data.SAMPLE NUMBER: Chronological order of samples. Ordinal data.DISTANCE FROM PATH: Measurement of distance travelled along a straight line from path, calculated using footsteps (1 footstep equals 0.6 m). Continuous data.INDIVIDUAL INSECTS COUNTED: Individual insects within a quadrat observed for 90 seconds. Ordinal data.RTUS COUNTED: Recognizable taxonomic units within a quadrat observed for 90 seconds. Ordinal data.<br>HYPOTHESIS<br>The woodlot will have a higher diversity of insects than the disturbed grassland.<br>PREDICTION<br>More RTUs will be observed in the woodlot than in the disturbed grassland.<br>METHODS<br>1. A direct line perpendicular to the section of path closest to Hoover road was walked.2. 1 person counted insects for 90 seconds per quadrat, timing themselves with a stopwatch.3. Observer used hands a pen to comb lightly through vegetation.<br>META DATA<br>1. A random number generator was used to decide the number of footsteps from the path and subsequently between each sample.2. Footsteps were estimated 0.6 but not measured.
DOI: 10.6084/m9.figshare.3859818.v1
title: BIOL 2050 WK4 STEP 2 DATA

description: VARIABLES<br>LOCATION: Saywell Woods, York University, ONSITE TYPE: The type of ecosystem in which data was collected. Categorical data.SAMPLE NUMBER: Chronological order of samples. Ordinal data.DISTANCE FROM PATH: Measurement of distance travelled along a straight line from path, calculated using footsteps (1 footstep equals 0.6 m). Continuous data.INDIVIDUAL INSECTS COUNTED: Individual insects within a quadrat observed for 90 seconds. Ordinal data.RTUS COUNTED: Recognizable taxonomic units within a quadrat observed for 90 seconds. Ordinal data.<br>HYPOTHESIS<br>The woodlot will have a higher diversity of insects than the disturbed grassland.<br>PREDICTION<br>More RTUs will be observed in the woodlot than in the disturbed grassland.<br>METHODS<br>1. A direct line perpendicular to the section of path closest to Hoover road was walked.2. 1 person counted insects for 90 seconds per quadrat, timing themselves with a stopwatch.3. Observer used hands a pen to comb lightly through vegetation.<br>META DATA<br>1. A random number generator was used to decide the number of footsteps from the path and subsequently between each sample.2. Footsteps were estimated 0.6 but not measured.
DOI: 10.7910/dvn/v1rjpf/lk0kim
title: snk20171116_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/fck5v3
title: snk20171030_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/xszmfb
title: snk20170906_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/revyvg
title: snk20170308_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/uqsnax
title: snk20170619_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859806
title: Poster: "At the entrances of zeolite nanochannels"

description: Poster describing structure, modification and physico-chemical processes at the entrance of zeolite L channels.(for references, see the links below)<br>The poster was presented at the 6th EuCheMS Congress in Seville (Sept. 11-15, 2016) and at the VI International Workshop on Oxide-Based Materials (Oxide2016) in Naples (Sept. 21-24, 2016).The poster is accompanied by two pdf files containing a short, non-technical summary of these results.
DOI: 10.7910/dvn/v1rjpf/yoiue9
title: snk20170827_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859806.v2
title: Poster: "At the entrances of zeolite nanochannels"

description: Poster describing structure, modification and physico-chemical processes at the entrance of zeolite L channels.(for references, see the links below)<br>The poster was presented at the 6th EuCheMS Congress in Seville (Sept. 11-15, 2016) and at the VI International Workshop on Oxide-Based Materials (Oxide2016) in Naples (Sept. 21-24, 2016).The poster is accompanied by two pdf files containing a short, non-technical summary of these results.
DOI: 10.7910/dvn/v1rjpf/yjr8aw
title: snk20171015_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859806.v1
title: At the entrances of zeolite nanochannels

description: Poster describing structure, modification and physico-chemical processes at the entrance of zeolite L channels.(for references, see the links below)<br>The poster was presented at the 6th EuCheMS Congress in Seville (Sept. 11-15, 2016) and at the VI International Workshop on Oxide-Based Materials (Oxide2016) in Naples (Sept. 21-24, 2016).The poster is accompanied by two pdf files containing a short, non-technical summary of these results.
DOI: 10.7910/dvn/v1rjpf/exqgv0
title: snk20171006_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859800
title: Monthly Wikipedia article quality predictions

description: Machine predicted quality levels of all articles in Wikipedia on a monthly basis. All datasets contain the following 6 columns.<br>page_id -- The page identifier<br>page_title -- The title of the article (UTF-8_with_underscores)<br>rev_id -- The most recent revision ID at the time of assessment<br>timestamp -- The timestamp when the assessment was taken (YYYYMMDDHHMMSS) <br>prediction -- The predicted quality class ("Stub", "Start", "C", "B", "GA", "FA", ...)<br>weighted_sum -- The sum of prediction weights assuming indexed class ordering ("Stub" = 0, "Start" = 1, ...)Predictions are made using the ORES "wp10" models for the relevant language. See [1] and [2] for more information.
DOI: 10.7910/dvn/v1rjpf/zzupeb
title: snk20170708_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859785
title: Bird Count in Grassland and Woodlot

description: Variables <br> Frequency: The frequency refers to number of times birds came over the region marked with the transect<br> Wind speed: Was collected in km/h by a phone app and then converted into the Beaufort scale<br> Species: Number of different kinds of birds observed<br> Distance: An estimate of a bird’s distance to the ground directly below it Hypothesis<br> If it rains, then more flocks of birds would gather because worms surface to the top and they are a good source of food for the birds. I predict that due to the high amounts of rain earlier in the day that there would be more birds present in big groups on the grassland. Methods<br> The experiment was done on grassland and woodlots found on York University property on September 26, 2016 around 2:45pm.There was a light drizzle of rain and at the start of the experiment, the temperature was around 15 degrees. A transect was placed on the ground and was 9m long for each replicate. For each replicate, 5 minutes were allocated for watching above for any birds. After the 5 minutes, species, frequency of birds and distance were jotted down and the next replicate was started. The first 5 replicates, were from the grassland and replicates 6-10 were in the woodlots. Sources of error<br> In the data collected, no birds were counted over each replicate but big groups of birds were seen feeding in the grasslands. When observing the frequency and birds, we may have been too close to the transect which may have scared the birds away. Only one type of bird was seen (seagulls) majority of the time and this may be due to the cooler weather. The cooler weather would force smaller birds such as sparrows to shelter such that they can conserve energy.
DOI: 10.7910/dvn/v1rjpf/znnphz
title: snk20171107_03.txt.gz

description: :unav
DOI: 10.6084/m9.figshare.3859785.v1
title: Bird Count in Grassland and Woodlot

description: Variables <br> Frequency: The frequency refers to number of times birds came over the region marked with the transect<br> Wind speed: Was collected in km/h by a phone app and then converted into the Beaufort scale<br> Species: Number of different kinds of birds observed<br> Distance: An estimate of a bird’s distance to the ground directly below it Hypothesis<br> If it rains, then more flocks of birds would gather because worms surface to the top and they are a good source of food for the birds. I predict that due to the high amounts of rain earlier in the day that there would be more birds present in big groups on the grassland. Methods<br> The experiment was done on grassland and woodlots found on York University property on September 26, 2016 around 2:45pm.There was a light drizzle of rain and at the start of the experiment, the temperature was around 15 degrees. A transect was placed on the ground and was 9m long for each replicate. For each replicate, 5 minutes were allocated for watching above for any birds. After the 5 minutes, species, frequency of birds and distance were jotted down and the next replicate was started. The first 5 replicates, were from the grassland and replicates 6-10 were in the woodlots. Sources of error<br> In the data collected, no birds were counted over each replicate but big groups of birds were seen feeding in the grasslands. When observing the frequency and birds, we may have been too close to the transect which may have scared the birds away. Only one type of bird was seen (seagulls) majority of the time and this may be due to the cooler weather. The cooler weather would force smaller birds such as sparrows to shelter such that they can conserve energy.
DOI: 10.7910/dvn/v1rjpf/c9exp1
title: snk20171005_03.txt.gz

description: :unav
DOI: 10.7910/dvn/v1rjpf/htwdso
title: snk20170627_03.txt.gz

description: :unav
DOI: 10.25549/one-ouc16636385
title: Vic S., letters (1957-1963)

description: Vic S., letters praising the photography in ONE magazine, discussing aspects of articles, and how to help lonely homosexuals connect. He also discusses not receiving issues and having his mail opened in Canada (1957-1963)
DOI: 10.15156/bio/sh1282204.08fu
title: SH1282204.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1282205.08fu
title: SH1282205.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1282206.08fu
title: SH1282206.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1282207.08fu
title: SH1282207.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1282208.08fu
title: SH1282208.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1282209.08fu
title: SH1282209.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.