PENENTUAN KADMIUM DALAM PRODUK PERIKANAN DENGAN GRAPHITE FURNACE ATOMIC ABSORPTION SPECTROMETRY
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
Penentuan kadmium dalam produk perikanan telah dilakukan menggunakan Graphite Furnace AtomicAbsorption Spectrometry (GF-AAS) dengan magnesium nitrat sebagai matrix modifier, platform atomizationtype A dengan sensitifitas yang tinggi untuk pengukuran kadmium, dan koreksi latar belakang Zeeman. Metodeanalisis telah divalidasi berdasarkan parameter-parameter kimia analitik. Sebanyak 0,5 g sampel produkperikanan didestruksi menggunakan microwave digestion systems dengan menambahkan 5 mL asam nitrat pekatdan 2 mL hidrogen peroksida 30%, kemudian larutan hasil destruksi diencerkan hingga 25 g. Dari larutan inidibuat sederet larutan untuk pengukuran secara adisi standar, dan diukur dengan GF-AAS. Akurasi metodedilakukan dengan menganalisis bahan acuan bersertifikat DORM 3 Fish Protein Certified Reference Materialfor Trace Metals dari National Research Council Canada dengan nilai recovery sebesar 99,9 ± 0,8%. Dari hasilpenelitian ini diperoleh kadar kadmium dan ketidakpastiannya sebesar 0,273 ± 0,025 mg kg-1berdasarkan beratkering.Kata kunci: GF-AAS, Microwave digestion systems, kadmium, validasi metoda
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it