Management of dyslipidemia in Poland: Interdisciplinary Expert Position Statement endorsed by the Polish Cardiac Society Working Group on Cardiovascular Pharmacotherapy. The Fourth Declaration of Sopot
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Food Effect on LDL-C Foods high in n-6 PUFA and/or MUFA and low in SFA; e.g., canola oil Moderate to large reduction Foods high in soluble fiber; e.g., psyllium, oats, and barley Moderate reduction Foods with added plant sterols or stanols Moderate reduction Flaxseeds (whole) Small to moderate reduction Soy protein Small to moderate reduction Tomatoes Small to moderate reduction Almonds Small reduction Fish No clear effect Decaffeinated coffee (in place of regular coffee) No effect Filtered coffee No effect Foods high in SFA or trans fatty acids (i.e., solid and tropical fats) Moderate to large increase Unfiltered coffee (in place of filtered coffee) Moderate to large increase Avocados Moderate to large reduction Turmeric Moderate to large reduction Hazelnuts Small to moderate reduction Pulses Small to moderate reduction Green tea At least small reduction Fiber, whole grains Small reduction Walnuts Small reduction Darker roast coffee No clear effect Fructose (in place of sucrose/glucose) No clear effect Marine oils (high in long-chain n-3 PUFA) Very small increase Free sugars Small increase Coffee (in place of tea) Small to moderate increase Garlic powder Small to moderate reduction Probiotics and prebiotics Small to moderate reduction Cumin Small to moderate reduction Ginger Small reduction Eggs Small increase Foods high in resistant starch Small reduction High-polyphenol olive oil (in place of low-polyphenol) Small reduction Foods high in a-linolenic acid, e.g., flaxseed oil No clear effect Foods high in medium-chain (in place on of long-chain) SFA No clear effect Grapefruits No effect Berries Small to moderate reduction Garlic Small to moderate reduction Black tea At least small reduction Dark chocolate/cocoa products At least small reduction Alcoholic drinks Small reduction Dairy products (all, high-fat, low-fat) No clear effect Grape polyphenols No clear effect Synbiotics No clear effect Whey protein No clear effect Fruit juice No effect Red meat No effect Sweeteners No effect MUFA -monounsaturated fatty acids; PUFA -polyunsaturated fatty acids; SFA -saturated fatty acids
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.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it