Notice bibliographique
Résumé
A dataset containing 117499 species occurrences available in GBIF matching the query: { "and" : [ "TaxonKey is Ficus L.", { "or" : [ "Country is Latvia", "Country is Luxembourg", "Country is Lithuania", "Country is Libya", "Country is Ecuador", "Country is Lesotho", "Country is Algeria", "Country is Venezuela (Bolivarian Republic of)", "Country is Montenegro", "Country is Dominican Republic", "Country is North Macedonia", "Country is Germany", "Country is Uzbekistan", "Country is Uruguay", "Country is Moldova, Republic of", "Country is Morocco", "Country is Mexico", "Country is United States of America", "Country is Malawi", "Country is Myanmar", "Country is Uganda", "Country is Ukraine", "Country is Ethiopia", "Country is Spain", "Country is Eritrea", "Country is Netherlands", "Country is Estonia", "Country is Namibia", "Country is Tanzania, United Republic of", "Country is New Caledonia", "Country is Georgia", "Country is New Zealand", "Country is United Kingdom of Great Britain and Northern Ireland", "Country is Nepal", "Country is Norway", "Country is France", "Country is Falkland Islands (Malvinas)", "Country is Finland", "Country is Poland", "Country is Guatemala", "Country is South Georgia and the South Sandwich Islands", "Country is Greece", "Country is Pakistan", "Country is Peru", "Country is Papua New Guinea", "Country is South Africa", "Country is Croatia", "Country is Romania", "Country is Hungary", "Country is Indonesia", "Country is Zimbabwe", "Country is Ireland", "Country is Austria", "Country is Argentina", "Country is India", "Country is Australia", "Country is Iraq", "Country is Iran (Islamic Republic of)", "Country is Yemen", "Country is Iceland", "Country is Azerbaijan", "Country is Italy", "Country is Bosnia and Herzegovina", "Country is Portugal", "Country is Afghanistan", "Country is Albania", "Country is Angola", "Country is Paraguay", "Country is Armenia", "Country is Japan", "Country is French Southern Territories", "Country is Belarus", "Country is Jordan", "Country is Brazil", "Country is Tajikistan", "Country is Bhutan", "Country is Tunisia", "Country is Turkmenistan", "Country is Canada", "Country is Türkiye", "Country is Bulgaria", "Country is Syrian Arab Republic", "Country is Bangladesh", "Country is Belgium", "Country is Bolivia (Plurinational State of)", "Country is Kyrgyzstan", "Country is Kenya", "Country is Czechia", "Country is Cyprus", "Country is Korea (Democratic People’s Republic of)", "Country is Sweden", "Country is Korea, Republic of", "Country is Slovenia", "Country is Slovakia", "Country is Kazakhstan", "Country is Serbia", "Country is Congo", "Country is Switzerland", "Country is Lebanon", "Country is Russian Federation", "Country is Colombia", "Country is China", "Country is Saudi Arabia", "Country is Chile" ] } ] } The dataset includes 117499 records from 380 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004341-150316153013904/datasets/export for details. Data from some individual datasets included in this download may be licensed under less restrictive terms.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,146 |
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 tête enseignante, 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 ».