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Record W4394561180 · doi:10.6084/m9.figshare.1596248

Naturally Occurring ecosystem "Trade-offs" affecting Solidago Canadensis & Symphyotrichum ericoides height and abundance on York University (Keele Campus)

2015· dataset· en· W4394561180 on OpenAlexaboutno aff
April Irums

Bibliographic record

VenueFigshare · 2015
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolidago canadensisAbundance (ecology)EcosystemEnvironmental scienceEcologyGeographyBiologyInvasive species

Abstract

fetched live from OpenAlex

Materials and Methods This study was conducted at the York University Keele campus in Toronto, Ontario (43.7731° N, 79.5036° W) at three different locations within the campus. The first location was the stong pond located within walking distance of The Pond Rd, the second location was Dan Iannuzzi Park Pond located on Cook Road and the final pond was the humber river- Black creek location within the black creek parkland found along Shoreham Dr. The three chosen locations consisted of similar vegetation and habitat characteristics. The duration of the study took place consistently over three weeks on October 1st, October 8 and October 15 with data collection once a week on Thursdays between 2:30 and 5:30pm. The average temperature in the month of October ranged from 14 to 18 degrees while weather conditions generally ranged from dry to mildly humid. All three of the ponds were visited in the designated three-hour time frame with data collection occurring for roughly thirty to forty minutes at each site and approximately ten to fifteen minutes were designated for travelling between the three locations. The two plant species studied were identified as Solidago Canadensis (Figure 6) and Symphyotrichum ericoides (Figure 5). The independent variables were abundance and distance from water and the dependent variable was the height of the plant. In preparing to sample solidago Canadensis and Symphyotrichum ericoides a transect was placed at the edge of the pond and measured out approximately 3 meters back from the edge of the water source. The intervals used were approximately 3 meters, 12 meters, and 15 meters. The quadrat was then placed at the 3-meter mark, subsequent repetitions involved moving the quadrant horizontally along the initially 3-meter mark (Figure 4). These repetition distances were calculated using a random number generator on Microsoft Excel, numbers 1 to 10 (measured in meters) were placed in the random generator to determine the next location of the replication. Using a second transect, distance of the second location was measured. A total of 3 reps were conducted at each measurement interval. The height of 5 different plants of the same species of solidago Canadensis and Symphyotrichum ericoides were measured using a transect and recorded. A total of 15 plants were measured per interval (n=15) per species over the course of 3 weeks. The abundance of both Solidago Canadensis and Symphyotrichum ericoides were counted, this was recorded. After each repetition, using a predetermined soil type guide, type of soil (qualitatively) was recoded (Figure 7). Next, the transect was measured from the edge of the water source back 12 meters and the same processes was repeated for 12-meters and 15-meters. The methods listed above were conducted at all three locations. After the collection of data, two different statistical tests were conducted on the data. Initially using a one-way ANOVA, the mean plant height (cm) in 3 different soil types (wet, weathered, dry) as a measure of distance away from a water source was measured. P values exceeding 0.05 were categorized as having no statistical difference. A two-tailed independent t-test was used to compare the mean plant height (cm) in 3 different soil types (wet, weathered, dry) between Solidago Canadensis and Symphyotrichum ericoides individually.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.216
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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