Query Results

Number of results 1000
Lowest scoring result -20.99768
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 2009/05/14 10:20:07 GMT
Time at which query was started
Finished at 2009/05/14 10:25:12 GMT
Time at which this file was written.
Feature score method scores_laplace_split
Name of the method used to calculate feature scores. Docstring for the method: For feature probabilities we use a Laplace prior, of 1 success and 1 failure in total, split between the classes according to size. This avoids problems with class skew.
Min Information Gain 2e-05
We exclude features with less than this value of Information Gain.
Base score -22.342841487
The log likelihood ratio of an empty article (one in which every feature failed to occur).
Prior score -8.90621167092
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 -1000.0
Default Naive Bayes classification threshold is zero. This threshold is the minimum log probability ratio for predicting an article to be relevant.
Minimum date 20080101
The minimum date considered when parsing Medline (both when making feature counts, and when querying)

Feature Statistics

Quantity Relevant Docs Irrelevant Docs
Number of documents 87 649233
Number of selected, occurring features 3243 37203
Total occurrences of selected features 7608 44352355
Selected features per Medline record 87.448 68.315
Of the considered feature types, 37294 features are selected out of 1302808 occurring at least once in training data. The aggressivity of selection is 34.933. The complete database lists 3703762 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
0.03 mesh Proteins 1782 4.87 44 5039
0.02 a c yeats 50988 11.28 17 0
0.02 issn 1362-4962 51097 5.49 23 956
0.02 w Protein 648 2.77 56 66196
0.02 w Proteins 1723 2.84 42 33653
0.02 mesh Databases, Protein 12064 5.27 19 927
0.02 mesh Sequence Analysis, Protein 51007 5.24 19 955
0.02 issn 1553-7358 125775 6.30 15 246
0.01 w Sequence 1953 2.88 30 18587
0.01 w Structural 1762 2.95 28 15791
0.01 w Genomics 15956 4.65 17 1503
0.01 w Functional 2242 2.49 34 32707
0.01 w Sequences 1767 3.11 25 11485
0.01 qual chemistry 616 2.13 51 93173
0.01 mesh Computational Biology 15970 4.02 18 3011
0.01 w Annotation 28383 5.12 14 743
0.01 w Prediction 10084 3.42 20 6259
0.01 mesh Protein Structure, Tertiary 1781 3.42 20 6276
0.01 w Structure 3866 2.42 28 26196
0.01 w Http 42206 4.33 15 1780