Spor Bilimleri Araştırmaları
Bibliographic record
Abstract
Atatürk ve Kişisel Gelişim Mikail TEL Refika KANATLI Çetin TAN Ahmet KORKMAZ Yüksek Şiddetli İnterval Antrenmanlar (YŞİA) ve Atletik Performans Fatma GÖZLÜKAYA GİRGİNER Yuksek İrtifada Antrenman ve Etkileri Tansu YAAN Mehmet Ali ÖZTÜRK Aydın İLHAN Sporcularda Sıvı Dengesi ve Fiziksel Performans Arasındaki İlişki Halit EGESOY Sporcularda Antrenman Maskesi Kullanımının Performans Üzerine Etkileri Ayşegül YAPICI ÖKSÜZOĞLU 400 Metre Engelli Koşuda Teknik ve Kinematik İnceleme Sibel TETİK DÜNDAR Futbolda Yaralanma Uzerine Araştırmalar Korhan KAVURAN 7-12 Yaş Cocuklarda Fizyolojik Farklılıklar ve Antrenmana Uyum (Atletizm Örneği) Ayşegül YAPICI ÖKSÜZOĞLU Sporda Ağrı, Şiddet ve Istırap Korhan KAVURAN Egzersizin Endokrin Sistem Üzerine Etkileri ve Hormonlar Mustafa Sencer ULAMA Mücahit SARİKAYA Mert EMBİYAOĞLU Sporcularda Uygulanan Farklı Masaj Tekniklerinin Performans ve Toparlanmaya Etkisi Üzerine Güncel Yaklaşımlar Fatma GÖZLÜKAYA GİRGİNER Tenisçilerin Duygusal Zeka Düzeylerinin İncelenmesi Aydın İLHAN Tansu YAAN Yaşlılarda Fizyolojik Değişimler ve Egzersiz Hakan YARAR
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".