Collecting data in the pond area and impermeable space for York University 2016
Notice bibliographique
Résumé
Description: · Following experiment was taken on October 26th, 2016, at York University for Ecology 2050. The data was gathered in both pond and impermeable space. The experiment took place from 2:45pm-4: 15pm, in clear weather conditions. The temperature ranged from 6-7 degrees Celsius. Data was collected in the pond area, followed by being collected in impermeable space (Baseball diamond). (The pond: 2:45-3:30pm, impermeable space: 3:30-4:15pm). Methods : Person 1 – Herbaceous Plants (Diana Bleyan) A 50m long transect was placed in a straight line on the ground of the pond and impermeable space. Every 2 meters along the transect, a 1mx1m quadrat was randomly placed (~1 meter from the transect) and number of exotic and native plants, and number of flowers was counted. The quadrat was placed in alternates on the left and right side of the transect. Person 2 – Woody Plants (Melinaz Barati) A 50m long transect was placed in a straight line on the ground of the pond and impermeable space. Every 2 meters along the transect, students have looked for a tree on either side of the transect within 0.5 meters from the transect. Person 3 – Vertebrates and Invertebrates (Nargol Ghazian) A 25 meter transect was placed in a straight line on the ground of the pond area and impermeable space, in order to provide the sense for a 25 meter radius. Vertebrates and invertebrates were observed using a naked eye. For invertebrates, the length of the transect was shortened to a 5 meter radius. Person 4 – Invertebrates (Noyell Sakthikumar) · A 25 meter transect was placed in a straight line on the ground of the pond area and impermeable area and 6 pan traps were placed along the transect (~1 meter away from each other along the length of the transect). Each pan trap was strategically placed with respect to color (the colors varied from blue to yellow to white). The soapy water was poured in each pan trap, covering half of the pan trap’s volume. All the traps were left for 45 minutes. · A 50m long transect was placed in a straight line on the ground of the pond area and impermeable area and a student conducted 10 sweep nets along the transect. The sweeps were done in a shape of infinity sign, 1 meter above the ground. Meta-data: Person 1 – Herbaceous Plants (Diana Bleyan) · Abundance.native.plants – native plants were defined as species within an observed quadrat, which grow naturally in a given region (Ontario, Canada). · Abundance.exotic.plants – exotic plants were defined as invasive species within an observed quadrat, which were introduced to a given region (Ontario, Canada). · Total.number.flowers (quadrat) – were counted as total number of flower heads within an observed quadrat. A flower head was considered to be at the top of the stem. Person 2 – Woody Plants (Melinaz Barati) · Abundance.woody.plants– a woody plant was considered as a tree higher than 1.5 meters in height. If no tree was observed within 0.5 meters from the transect, students recorded 0. · Canopy.cover– was estimated in %, by holding a square (created by hands, approximately 3cmx3cm) and measuring how much of the square area was filled with canopy of the tree. · Ground.cover – was estimated in %, by holding a square (created by hands, approximately 3cmx3cm) and measuring how much of the square area contains vegetation. · Total.flower.numbers (transect)– was counted, within 0.5 meter distance from the observed tree/trees. A flower was considered to be any plant that contained a flower head, attached to the top of the stem. Person 3 – Vertebrates and Invertebrates (Nargol Ghazian) · Abundance.invertebrate.observed – the variety of invertebrates observed, consisted of mosquitos, bugs and snails. · Abundance.vertebrates observed, consisted of birds (including Seagulls and ducks). · Abundance.human was separated from the rest of the vertebrate species not part of our lab. · Vertebrate.richness is the number of different species represented in a given landscape or region. Person 4 – Invertebrates (Noyell Sakthikumar) · Abundance.invertebrates.pantraps – the number of invertebrates trapped in a soapy water of a pan trap · Abundance.invertebrates.sweeps – the number of invertebrates trapped in a sweep net (at the end of sweeping along the 50m transect)
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,141 | 0,042 |
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 ».