The Global Soundscapes Project: overview of datasets and meta-data
Notice bibliographique
Résumé
This is an overview of the soundscape recording datasets that have been contributed to the Global Soundscapes Project, as well as associated meta-data. The audio recording criteria justifying inclusion into the current meta-dataset are: Stationary (no towed sensors or microphones mounted on cars) Passive (no human disturbance by the recordist) Ambient (no focus on a particular species or direction) Recorded over multiple sites of a region and/or days The individual columns are described as follows. General: ID: primary key name: name of the dataset subset: incremental integer that can be used to distinguish sub-datasets collaborators: full names of people deemed responsible for the dataset, separated by commas date_added: when the dataset was added Space: realm_IUCN: realm from IUCN Global Ecosystem Typology (v2.0) (https://global-ecosystems.org/) medium: the physical medium the microphone is situated in GADM0: for terrestrial locations, Database of Global Administrative Areas level 0 unit as per https://gadm.org/ GADM1: for terrestrial locations, Database of Global Administrative Areas level 1 unit as per https://gadm.org/ GADM2: for terrestrial locations, Database of Global Administrative Areas level 2 unit as per https://gadm.org/ IHO: International Hydrographic Organisation sea area as per https://iho.int/ latitude_numeric_region: study region approximate centroid latitude in WGS84 decimal degrees longitude_numeric_region: study region approximate centroid longitude in WGS84 decimal degrees topography_min_m: minimum elevation of sites from sea level topography_max_m: maximum elevation of sites from sea level ground_distance_m: vertical distance of microphone from land ground or ocean floor freshwater_depth_m: vertical distance from water surface for freshwater datasets sites_number: number of sites sampled Time: days_number_per_site: typical number of days sampled per site (or minimum if too variable) day: whether the sites were sampled during daytime night: whether the sites were sampled during nighttime twilight: whether the sites were sampled during twilight warm_season: whether the warm season was sampled. Only outside tropics (https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification) cold_season: whether the cold season was sampled. Only outside tropics (https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification) dry_season: whether the dry season was sampled. Only for tropics (https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification) wet_season: whether the wet season was sampled. Only for tropics (https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification) year_start: starting year of the sampling year_end: ending year of the sampling schedule: description of the sampling schedule, free text recording_selection: criteria used to temporally select recordings (e.g., discarded rainy days) Audio: high_pass_filter_Hz: lower frequency of the high-pass filter sampling_frequency_kHz: frequency the microphone was sampled at audio_bit_depth: bit depth used for encoding audio recorder_model: recorder model used microphone: microphone used recordist_position: position of the recordist relative to the microphone during sampling Others: comments: free-text field URL_project: internet link for further information URL_publication: internet link of the corresponding publication More information on the project can be found here: https://ecosound-web.uni-goettingen.de/ecosound_web/project/gsp
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 | 0,003 | 0,001 |
| 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 | 0,006 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,003 | 0,018 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».