{"id":"W1595429343","doi":"10.2196/medinform.3740","title":"Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users","year":2015,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine","keywords":"Session (web analytics); Computer science; Information retrieval; MEDLINE; Query expansion; Web search query; World Wide Web; Search engine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002806226,0.0002805767,0.0005842984,0.002182075,0.0003774384,0.0009679229,0.0005009777,0.0004395852,0.001483747],"category_scores_gemma":[0.02312278,0.0001868679,0.0004772411,0.001395803,0.0003141192,0.001214477,0.0008307366,0.0004196119,0.0006877319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002809413,"about_ca_system_score_gemma":0.0004464073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001976423,"about_ca_topic_score_gemma":0.002496406,"domain_scores_codex":[0.9973482,0.0008326371,0.0005190307,0.0005093914,0.0005873625,0.0002033928],"domain_scores_gemma":[0.9665453,0.0203185,0.005989957,0.001661035,0.003474522,0.002010715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001374612,0.0004590387,0.926329,0.0004378704,0.000209632,0.0002909325,0.00591398,0.0002338681,0.004280377,0.00006138222,0.001257427,0.05915178],"study_design_scores_gemma":[0.00002641417,0.0009148429,0.9906474,0.00002606887,0.00007859207,0.0006507613,0.003044216,0.001602541,0.001392375,0.00005291893,0.001523876,0.00003990521],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978095,0.000195793,0.0004504209,0.0000516255,0.000004220317,0.00006859563,0.0008570615,0.00007897816,0.0004838453],"genre_scores_gemma":[0.9964848,0.0001760982,0.001248473,0.00006521987,0.0000175514,0.0001409498,0.001250098,0.00002235138,0.0005945613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9990321,"threshold_uncertainty_score":0.01484096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08112951096715199,"score_gpt":0.3589180753614555,"score_spread":0.2777885643943035,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}