Bibliographic record
Abstract
Como bien sabemos, la identificacion de aquellos individuos capaces de experimentar emociones conscientes es clave para determinar que seres merecen ser considerados moralmente.1 Esto es defendible desde distintos enfoques normativos (vease Horta, 2009). Sin embargo, dado que no somos capaces de mesurar directamente que individuos son conscientes, dependemos de otro tipo de informacion, que podemos denominar indirecta, para evaluar la probabilidad de que un individuo sea capaz de darse cuenta en mayor o menor medida de aquello que le sucede. Este enfoque reduccionista, a pesar de ser la herramienta mas fiable que disponemos para esta tarea, deviene mas cuestionable cuando consideramos el caso de individuos incapaces de utilizar alguna de las formas de lenguaje humano (Sanchez Suarez, 2010). Este hecho es fundamental para comprender que desde el ambito cientifico aun existan posturas desde las que se argumenta Received: 07-05-2012 Accepted: 15-05-2012 ?Mas que pacientes morales?
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".