Bibliographic record
Abstract
CĂlem tohoto pĹĂspÄvku bylo posoudit, do jakĂŠ mĂry vznik mimoĹĂĄdnĂŠ situace, kterou v roce 2020 a 2021 zpĹŻsobil SARS-CoV-2, ovlivĹuje vĂ˝nosovĂŠ oceĹovĂĄnĂ. Dopady na vĂ˝nosovĂŠ oceĹovĂĄnĂ podnikatelskĂ˝ch subjektĹŻ mohou bĂ˝t neutrĂĄlnĂ, negativnĂ nebo pozitivnĂ podle toho, jak bylo pĹĂsluĹĄnĂŠ odvÄtvĂ ovlivnÄno SARS-CoV-2. V pĹĂpadÄ negativnĂho dopadu dochĂĄzĂ k poklesu vĂ˝nosĹŻ oproti plĂĄnovanĂ˝m hodnotĂĄm v rĂĄmci vĂ˝nosovĂŠho oceĹovĂĄnĂ, a tedy i ke snĂĹženĂ hodnoty vĂ˝nosovÄ oceĹovanĂŠho podnikatelskĂŠho subjektu. Intenzita tohoto negativnĂho vlivu bude vychĂĄzet ze schopnosti danĂŠho subjektu vypoĹĂĄdat se s dopady krize neboli z pĹĂsluĹĄnĂŠho vnitĹnĂho potenciĂĄlu tohoto oceĹovanĂŠho subjektu, a takĂŠ na tom, zda krize SARS-CoV-2 postihla obdobĂ v rĂĄmci prvnĂ fĂĄze oceĹovĂĄnĂ nebo aĹž v rĂĄmci pokraÄujĂcĂ hodnoty. NegativnĂ dopad se projevuje pĹedevĹĄĂm v rĂĄmci strategickĂŠ analĂ˝zy i analĂ˝zy finanÄnĂ. DochĂĄzĂ k odliĹĄnĂŠmu vĂ˝voji trhu jako celku, ale ke zmÄnĂĄm dochĂĄzĂ takĂŠ vlivem mÄnĂcĂch se konkurenÄnĂch pozic. I pĹes krizĂ zpĹŻsobenĂŠ problĂŠmy mĂĄ vĂ˝nosovĂŠ oceĹovĂĄnĂ svĂŠ mĂsto a svojĂ vypovĂdacĂ schopnost, pĹiÄemĹž je tĹeba posĂlit analĂ˝zu vnitĹnĂho potenciĂĄlu oceĹovanĂŠho podnikatelskĂŠho subjektu z hlediska schopnosti Äelit pĹĂpadnĂŠ krizi.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".