Lab 2, Field Dataset 1: Utilizing Quadrats to Examine the Abundance and Diversity of Plant Species Within the Danby Woods Grasslands.
Notice bibliographique
Résumé
Meta Data Attributes Description Quadrat Number (n): A square, metal quadrat (1m x 1m) was placed randomly in the grassland 25 times. The quadrat placed was divided into 4 subunits (0.5m x 0.5m). Only the bottom right unit of space was examined and displayed in this data set. Each unit of space observed is affiliated with a number (n). Total Abundance of Plants The amount of every plant present in the specific subunit of the quadrat (including grass and other species of plants). The amount of grass in the specific subunit of the quadrat was estimated by counting the number of clustered grass sprouting from the same root and location. The amount of individual plants of a different species (not grass) was counted one by one by the experimentors. Total Number of Different Plant Species: The amount of different plant species observed by the experimentors within the specific quadrat. Plants were determined to be of a different species based on observable morphological differences.Total Cover of Vegetation(%): The percentage of the specific subunit quadrat covered by any vegetation (including grass and other plant species). The percentage was an estimation made by the experimentors through close examination of the quadrat. Total Cover of Grasses(%): The percentage of the specific subunit quadrat covered by only grass. The percentage was an estimations made by the experimentors through close examination of the quadrant.Methods: To record this dataset, quadrats were placed randomly in the grassland, considering that there was a consistent range of environmental diversity. The quadrat used was a metal squared frame that measured the area of a square meter (1m x 1m). Random sampling was used; 1st quadrat (n=1), 2nd quadrat (n=2), and so on until n reached 25. This format of sampling was used to avoid and biases in the results. Each quadrat was placed in a random location within the designated grassland area mentioned by the TA. The quadrat was divided into subunits of 4 (0.5m x 0.5m) and the bottom right corner was used everytime to examine its' contents for the abundance, number of species, total cover of vegetation, and total cover of grass. Also the data collected is numerical. Study Site: This dataset was collected in the grassland near Danby Woods at York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. This study was conducted on Thursday September 22nd, 2016 from about 2:45-3:30pm. The weather was mostly sunny, but for a short period of time (10 mins) there was a drizzle.Hypothesis: If the presence of grass and other species of plants are greater in shadier area compared to those exposed to the sun, then seed germination in a sunny habitat will be limited by the lack of moisture present in comparison to shadier habitats.Prediction:1. Little range of plant growth and dispersion in sunny parts of the grassland.2. The plants existing in the sunny patches of the grassland would mostly consist of dried out plants.3. Shadier areas will consist of more species heterogeneity and a widely dispersed plant growth.Group Members: Keerthana, Matthew, Abesan, and Andrew
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,022 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».