The Morphology of the tG- Stem in Hebrew and Tirgaltî in Hos 11:3
Bibliographic record
Abstract
TheMasoreticText(MT)ofHos11:3areads ְוָאֹנִכי ִתְרַגְּלִתּי ְלֶאְפַרִים Although the entire verse is difficult, the form and . ָק ָחם ַעל־ ְזרוֹעֹ ָתיו meaning of the word ִתּ ְר ַגּ ְל ִתּי (tirgaltî) has been especially problematic for interpreters from the beginning of attempts to These difficulties emerge from the morphological peculiarities of the word, as well as from the lexicographic difficulties it presents. The present article proceeds from the conviction that an adequate solution to the second problem—lexicography—requires a sufficiently comprehensive answer to the first problem—morphology. Unfortunately, although we remain optimistic that a lexicological answer to the questionable semanticfieldofthewordִתְּרַגְּלִתּי mayeventuallybegiven,suchan explanation cannot be made without significant exegetical elaboration, space for which is unavailable in the confines of the present article. Therefore, the explicit goal of the present article is to propose a solution to the former problem—the morphology of . ִתּ ְר ַגּ ְל ִתּי
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".