Bibliographic record
Abstract
Among other things, Thomson's ISI Web of Knowledge is responsible for bringing the Impact Factor into mainstream use in the academy and the journal-publishing world. I have expressed on numerous occasions that I am skeptical of the Impact Factor and its influence on where authors/researchers choose to publish. However, that is a subject for further discourse in a future editorial. For this editorial I am selecting from other data that Thomson also supplies: citation data to specific papers. The Peer-Reviewed Communications Committee suggested that we identify and recognize some of the papers that have had a particularly significant effect on our knowledge by being cited by other researchers. I took up this challenge and plunged into the ISI Web of Science citation data for the Journal of Food Science. I looked at data from 2003 since that would give some time for the papers to be out there and be cited. It is my intention to do this annually immediately following the IFT Annual Meeting so that we can congratulate the authors and encourage other authors to submit their manuscripts to JFS. As of June, 2006, there were 346 citations to the top 40 papers that were cited from publishing year 2003, an average impact factor of 8.65! In the top 40 papers by citation numbers, there were 13 in cood chemistry, 10 in Food engineering, 8 in sensory and nutritive properties, 6 in food microbiology and 3 in concise reviews. Given the number of papers published in each section, one might expect such a distribution of citation excellence. The number 1 cited paper for 2003 is from the Food Chemistry section: “A Novel Technique for Limitation of Acrylamide Formation in Fried and Baked Corn Chips and in French Fries,” authored by MY Jung, DS Choi, and JW Wu of the Dept. of Food Science and Technology and Biotechnology at Woosuk Univ., Samrea, Jeonbuk, South Korea [JFS 68(4):1287-90]. This paper has been cited 46 times! The second most cites was a paper cited 15 times, and the least cited in the top 40 was cited 6 times. Congratulations to Drs. Jung, Choi and Wu for their excellent paper. The top cited papers in the other sections of JFS are: Food Engineering: “Oxidative Stability, Structure, and Physical Characteristics of Microcapsules Formed by Spray Drying of Fish Oil with Protein and Dextrin Wall Materials,” by Y Kagami, S Sugimura, N Fujishima, K Matsuda, T Kometani, and Y Matsumura [JFS 68(7):2248-55]. Food Microbiology: “Biotransformation of Isoflavones by Bifidobacteria in Fermented Soymilk Supplemented with D-Glucose and L-Cysteine,” by D Tsangalis, JF Ashton, AEJ McGill, and NP Shah [JFS 68(2):623-31]. Sensory and Nutritive Properties: 2 papers tied: “Effect of Storage Conditions on Quality Characteristics of Bologna Sausages Made with Citrus Fiber,” by JM Fernandez-Gines, J Fernandez-Lopez, E Sayas-Barbera, E Sendra, and JA Perez-Alvarez [JFS 68(2):710-5], and “Dual Fortification of Salt with Iodine and Encapsulated Iron Compounds: Stability and Acceptability Testing in Morocco and Cote d'Ivoire,” by R Wegmuller, MB Zimmerman, and RF Hurrell [JFS 68(6):2129-35]. Concise Reviews: “Active Packaging Technologies with an Emphasis on Antimicrobial Packaging and its Application,” by P Suppakal, J Miltz, K Sonneveld, and SW Bigger [JFS 68(2):408-20]. Thank you to the authors for submitting their papers to JFS. I invite you to submit your research to JFS. Maybe I'll be citing your paper in this column in three years! Have a great summer
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".