{"id":"W2734027756","doi":"10.18438/b8zh3r","title":"Web-Scale Discovery Services Retrieve Relevant Results in Health Sciences Topics Including MEDLINE Content","year":2017,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information retrieval; Computer science; MEDLINE; Relevance (law); Medical library; World Wide Web; Scale (ratio); Library science; Data science; Political science; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.007515673,0.000112722,0.0001898593,0.0002649321,0.003166536,0.0006393542,0.0005195111,0.00009971637,0.00005633116],"category_scores_gemma":[0.009963512,0.00008813795,0.00001957427,0.0003532357,0.000204464,0.2328018,0.0002957844,0.0005965639,0.00005963889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007971679,"about_ca_system_score_gemma":0.003137377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00105358,"about_ca_topic_score_gemma":0.0000464931,"domain_scores_codex":[0.9967335,0.0008624516,0.001078698,0.000240354,0.0005502942,0.000534716],"domain_scores_gemma":[0.9944261,0.003415299,0.001345906,0.000403797,0.0001141326,0.0002947865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00900797,0.0004782575,0.6438801,0.01488712,0.00002625669,0.00001852153,0.06061013,0.0004095549,0.0002706973,0.1156181,0.05674628,0.0980471],"study_design_scores_gemma":[0.001168153,0.0004600257,0.3012201,0.00455861,0.000003443341,0.000003220148,0.02055754,0.01666109,0.0001335863,0.0002133008,0.6548347,0.0001862867],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1828313,0.0006795216,0.0001958349,0.8058298,0.0009064986,0.00098646,0.00004216807,0.00005714911,0.008471299],"genre_scores_gemma":[0.8496904,0.01542383,0.006614096,0.1259408,0.0004705221,0.00009204705,0.00007614392,0.000007327519,0.001684826],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.679889,"threshold_uncertainty_score":0.998376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1695337392168436,"score_gpt":0.4646248664176725,"score_spread":0.2950911272008289,"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."}}