More than 160 near Earth asteroids observed in the EURONEAR network
Notice bibliographique
Résumé
Context. The EUROpean Near Earth Asteroid Research (EURONEAR) is a network which envisions to bring some European contributions into the general context traced by the Spaceguard Foundation which was carried out during the last 15 years mainly by the US with some modest European and amateur contributions. Aims. The number of known near Earth asteroids (NEAs) and potentially hazardous asteroids (PHAs) has increased tremendously, mainly thanks to five major surveys all focused on the discovery of new bodies. But also other facilities are required to follow-up and improvement the orbital parameters and to study the physical properties of the known bodies. These goals are better achieved by a co-ordinated network such as EURONEAR. Methods. Astrometry is mandatory in order to acquire the positional information necessary to define and improve orbits of NEAs and PHAs and to study their trajectories through the solar system, especially in the vicinity of Earth. Photometry is required to derive some physical information about NEAs and PHAs. In order to achieve these objectives, the main method of research of the EURONEAR is the follow-up programme of objects selected by a few criteria, carried out mostly at 1 m-class telescopes endowed with medium and large field cameras. Results. 162 NEAs summing more than 1500 individual positions were observed for a total time of 55 nights in both visiting mode and regular runs using nine telescopes located in four countries. The observations were reduced promptly and reported to the Minor Planet Centre (MPC) which validated and included them in the MPC and NEODyS databases following the improvement of their orbital elements. For one binary NEA we acquired photometry and were able to determine its orbital and rotational periods. Complementary to the follow-up work, as many as 500 unknown moving objects consistent with new Main Belt asteroids and one possible NEA were discovered in the analyzed fields. Conclusions. Our positions present 1 precision with an accuracy of 0.2–0.4, sufficient for achieving our immediate main goals. The observations and data reduction were conducted by our network members, which included some students and amateurs supervised by professional astronomers. In most cases, we increased the observational arcs decreasing the uncertainties in the orbits, while in some cases the new positions allowed us to recover some bodies endangered to be lost, defining their orbits.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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; 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 ».