Bibliographic record
Abstract
Apres la mort d'Omar Bongo, le 8 juin 2009, Andre Mba Obame presente sa candidature a l'election presidentielle du 30 aout. Il demande a genoux, l’absolution pour le mal fait aux Gabonais en 42 ans par le systeme PDG. Au terme du scrutin, il est declare battu. Un an apres, les services secrets francais reconnaissent qu’AMO fut le vrai vainqueur de ladite presidentielle. Il s’autoproclame ainsi Chef de l'Etat. C'est le debut de la fin. Terrasse par une maladie etrange, Andre Mba Obame court les medecins et les guerisseurs traditionnels. Il decede le 12 avril 2015, a Yaounde(Cameroun). Que retiendront les Gabonais d'Andre Mba Obame? Du jeune prodige forme a Laval et a la Sorbonne, protege d'Omar Bongo, a l'opposant malade de ces dernieres annees, en passant par sa victoire a la presidentielle de 2009 ? Andre Mba Obame aura fortement influence les trente dernieres annees de la politique gabonaise. Stratege politique redoutable bourre de talents, un animal politique tres intelligent au cerveau d'un brin manipulateur. Depuis l’existence du Gabon, jamais les obseques d’un homme politique, a tous les niveaux, auront mobilise autant de Gabonais.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.109 | 0.038 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".