The State of Phylogenetic Analysis: Narrow Visions and Simple Answers—Examples from the Diptera (flies)
Notice bibliographique
Résumé
The order Diptera is remarkably diverse, not only in species but in morphological variation in every life stage, making them excellent candidates for phylogenetic analysis. Such analysis has been hampered by methods that have severely restricted character state interpretation. Morphological-based phylogenies should be based on a deep understanding of the morphology, development and function of character states, and have extensive outgroup comparisons made to determine their polarity. Character states clearly vary in their value for determining phylogenetic relationships and this needs to be studied and utilized. Characters themselves need more explicit discussion, including how some may be developmentally or functionally related to other characters (and potentially not independent indicators of genealogical relationship). The current practice by many, of filling a matrix with poorly understood character states and highly limited outgroup comparisons, is unacceptable if the results are to be a valid reflection of the actual history of the group.Parsimony analysis is not an objective interpretation of phylogenetic relationships when all characters are treated as equal in value. Exact mathematical values applied to characters are entirely arbitrary and are generally used to produce a phylogeny that the author considers as reasonable. Mathematical appraisal of a given node is similarly inconsequential because characters do not have an intrinsic mathematical value. Bremer support, for example, provides values that have no biological reality but provide the pretence of objectivity. Cladists need to focus their attention on testing the validity of each synapomorphy proposed, as the basis for all further phylogenetic interpretation, rather than the testing of differing phylogenies through various comparative programs.Current phylogenetic analyses have come to increasingly depend on DNA sequence-based characters, in spite of their tumultuous history of inconsistent results. Until such time as sequences can be shown to produce predictive phylogenies (i.e., using Hennigian logic), independent of morphological analysis, they should be viewed with caution and certainly not as a panacea as they are commonly portrayed.The purported comprehensive analyses of phylogenetic relationships between families of Diptera by Wiegmann et al. (2011) and Lambkin et al. (2013) have serious flaws and cannot be considered as the "Periodic Table" of such relationships as originally heralded.Systematists working on Diptera have a plethora of complex and informative morphological synapomorphies in every life stage, either described or awaiting study. Many lineages have the potential of providing a wealth of evolutionary stories to share with other biologists if we produce stable phylogenies based on weighted synapomorphies and interpreted to elucidate the zoogeographic and bionomic divergence of the group. Some lineages are devoid of convincing synapomorphies and, in spite of our desires, should be recognized as being largely uninterpretable.
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 | 0,021 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,006 | 0,043 |
| Communication savante | 0,013 | 0,034 |
| Science ouverte | 0,002 | 0,009 |
| Intégrité de la recherche | 0,008 | 0,016 |
| 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 ».