Bibliographic record
Abstract
The sections in this article are: 1 A Brief Historical Perspective and Prelude to the Review 2 Physiological Role of The Cardiac Na+-Ca2+ Exchanger 3 Reverse Na+-Ca2+ Exchange as A Trigger for SR Ca2+ Release 4 Digitalis Effects 5 Immunolocalization 6 Transport Properties 6.1 Stoichiometry 6.2 Transport Mechanism 6.3 Turnover Rates and Exchanger Density 6.4 Ion Selectivity 6.5 Temperature Dependence 7 Molecular Biology of the Na+-Ca2+ Exchanger 7.1 The Prototypical Canine Cardiac Na+-Ca2+ Exchanger 7.2 The Exchanger Superfamily 7.3 Topology of the Na+-Ca2+ Exchanger 7.4 The Calx-α and Calx-β Repeats 7.5 Alternative Splicing of Na+-Ca2+ Exchangers 8 Regulation of Na+-Ca2+ Exchange 8.1 Ionic Regulation 8.1.1 Nai+-Dependent Inactivation 8.1.2 Cai+-Dependent Regulation 8.2 Structure–Function Relationships of Ionic Regulation 8.2.1 The XIP Region 8.2.2 The Regulatory Ca2+ Binding Site 8.3 Regulation by Phosphorylation 8.4 Regulation by PIP2 8.5 Regulation by pH 8.6 Cytoskeletal Interactions 9 Pharmacology of Na+-Ca2+ Exchange 9.1 The Exchanger Inhibitory Peptide, XIP 9.2 Other Peptide Inhibitors 9.3 KB-R7943 9.4 Other Inhibitors 10 Studies in Transgenic Mice 11 Adenoviral Transfection of Na+-Ca2+ Exchange Proteins 12 Antisense Oligonucleotides 13 Frequency-Dependent Behavior of Na+-Ca2+ Exchange 14 Developmental Changes 15 Species Differences 16 Pathophysiological Alterations in Na+-Ca2+ Exchange 16.1 Contribution of Na+-Ca2+ Exchange to Cardiac Injury 16.2 Alterations in Na+-Ca2+ Exchange Levels 17 Summary
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".