Query Results

Number of results 1000
Lowest scoring result 31.33012
Abstracts of results results.html
Complete abstracts of the articles in Medline predicted to be relevant (limited number per page).
Abstracts of all results ZIP file or all_results.html
All result abstracts on a single page. (can take a long time to load - downloading the zip file is recommended)
Abstracts of input examples inputs.html
Complete abstracts of the Medline records given as relevant training examples. They have been ranked by classifier scores.
PubMed IDs of results results.txt
PubMed IDs and scores of classifier predictions, ranked by decreasing score.
PubMed IDs of inputs inputs.txt
PubMed IDs and scores of the relevant training examples.
Started at 2009/02/25 08:40:52 GMT
Time at which query was started
Finished at 2009/02/25 08:52:13 GMT
Time at which this file was written.
Feature score method scores_bgfreq
Name of the method used to calculate feature scores. Docstring for the method: The prior is 'background frequency' successes, out of 1 total occurrence in each class.
Min Document Frequency 2
We exclude features occurring fewer than this many times in the data
Base score -14.8549200571
The log likelihood ratio of an empty article (one in which every feature failed to occur).
Prior score -6.15712956198
The log of the prior probability ratio for an article being relevant versus irrelevant (added to log likelihood ratio to obtain the final score). Equals the logit of the estimated prevalence of relevant articles in Medline (which may be estimated from the input size or specified separately).
Limit 1000
The maximum number of results to include.
Threshold -30.0
Default Naive Bayes classification threshold is zero. This threshold is the minimum log probability ratio for predicting an article to be relevant.

Feature Statistics

Quantity Relevant Docs Irrelevant Docs
Number of documents 36002 16995974
Number of selected, occurring features 10656 41209
Total occurrences of selected features 586213 230416234
Selected features per Medline record 16.283 13.557
Of the considered feature types, 41209 features are selected out of 43325 occurring at least once in training data. The aggressivity of selection is 1.051. The complete database lists 43326 potential features.

Features with high TF.IDF

Features with TF.IDF above 0.2 or 0.3 could make good keywords. TF.IDF is term frequency times inverse document frequency, where we treat the set of input citations as a single document

TF-IDF Type Term Term ID Score Pos Neg
0.36 mesh Alzheimer Disease 10583 17.99 36002 9388
0.08 mesh Aged 1395 2.52 20891 1700316
0.06 mesh Aged, 80 and over 11276 2.76 9429 375119
0.06 mesh Amyloid beta-Protein 28044 6.15 4705 5449
0.05 mesh Brain 419 2.69 7345 290426
0.04 mesh Neuropsychological Tests 14882 4.16 4081 33835
0.04 qual psychology 5147 2.04 6911 506848
0.04 qual pathology 4121 1.32 10056 1599417
0.04 qual metabolism 1195 0.82 12280 3160098
0.03 mesh Middle Aged 8417 0.89 10583 2476859
0.03 mesh Amyloid beta-Protein Precursor 25607 5.94 2526 3378
0.03 mesh Dementia 3643 4.19 3071 23903
0.03 mesh Female 5165 0.64 15807 4969524
0.03 mesh Male 5429 0.62 15767 5021002
0.03 mesh Apolipoproteins E 25324 5.08 2461 7746
0.03 qual physiopathology 6635 1.21 6528 1051880
0.03 qual genetics 4402 0.90 7782 1710833
0.03 mesh Cognition Disorders 4600 3.98 2768 26497
0.03 qual diagnosis 647 0.95 7171 1497797
0.03 mesh Humans 6971 2.67 34457 10334034