Bibliographic record
Abstract
Part I TABLE---------------------------------------------------------------------- voice 1: Out of this haunted land words rise up ---------------------------------------------------------------------- voice 2: maspik, enough, kefaya ---------------------------------------------------------------------- v1: kefaya, enough, maspik ---------------------------------------------------------------------- v2: In this land, the ground is haunted and each wind has a name ---------------------------------------------------------------------- v1: shard, rih teqil, maltam (pause) shard ---------------------------------------------------------------------- v2: shard: vent chaud charge de sable, a hot sand-filled wind ---------------------------------------------------------------------- v1: rih teqil ---------------------------------------------------------------------- v2: rih teqil: vent violent et dangereux, a violent and dangerous wind ---------------------------------------------------------------------- v1: maspik, enough, kefaya ---------------------------------------------------------------------- v2: this cannot be changed. ---------------------------------------------------------------------- v1: Ley? Why? Lama? ---------------------------------------------------------------------- (Pause) ---------------------------------------------------------------------- v2: There is no peace without recognition ---------------------------------------------------------------------- Between the earth mixed with bone and blood and the sea we share and fear, the winds shift and shift again there is no peace without memory ---------------------------------------------------------------------- v1: without memory TABLE---------------------------------------------------------------------- v2: and these turbulent times offer no peace ---------------------------------------------------------------------- v1: no peace ---------------------------------------------------------------------- v2: without recognition ---------------------------------------------------------------------- v1: without recognition ---------------------------------------------------------------------- v1 & v2: I know you/ v1: 'airfaki ---------------------------------------------------------------------- v1 & v2: I know you/ v2: ani makira otakh ---------------------------------------------------------------------- v1 & v2: This is the sound of peace ---------------------------------------------------------------------- v1: kol ha shalom ---------------------------------------------------------------------- v2: the sound of peace/ sott el salaam Part II TABLE---------------------------------------------------------------------- v2: Two women ---------------------------------------------------------------------- v1: two women, between land and sea, ---------------------------------------------------------------------- v2: In the middle of the night, Each hears a small voice calling her, ---------------------------------------------------------------------- v1 & v2: Mama Ima ---------------------------------------------------------------------- v2: this small voice says (Pause) Some part of us has let them down, some part of us is no longer ---------------------------------------------------------------------- mama ---------------------------------------------------------------------- v1: Ima ---------------------------------------------------------------------- v2: to anyone. …
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.018 |
| Insufficient payload (model declined to judge) | 0.036 | 0.012 |
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".