REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE <br>“Physical activity in a healthy lifestyle”
Bibliographic record
Abstract
ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Niźnikowska E. REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”. Health Problems of Civilization. 2014;8(3):44-44. doi:10.5114/hpc.2014.57085. APA Niźnikowska, E. (2014). REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”. Health Problems of Civilization, 8(3), 44-44. https://doi.org/10.5114/hpc.2014.57085 Chicago Niźnikowska, Ewelina. 2014. "REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”". Health Problems of Civilization 8 (3): 44-44. doi:10.5114/hpc.2014.57085. Harvard Niźnikowska, E. (2014). REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”. Health Problems of Civilization, 8(3), pp.44-44. https://doi.org/10.5114/hpc.2014.57085 MLA Niźnikowska, Ewelina. "REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”." Health Problems of Civilization, vol. 8, no. 3, 2014, pp. 44-44. doi:10.5114/hpc.2014.57085. Vancouver Niźnikowska E. REPORT FROM THE 3RD INTERNATIONAL SCIENTIFIC CONFERENCE “Physical activity in a healthy lifestyle”. Health Problems of Civilization. 2014;8(3):44-44. doi:10.5114/hpc.2014.57085.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.353 | 0.238 |
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".