{"id":"W2008169899","doi":"10.2196/medinform.2671","title":"An Intelligent Content Discovery Technique for Health Portal Content Management","year":2014,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Australian Government","keywords":"Computer science; Content (measure theory); Content management; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.0008681024,0.0001766277,0.0002617539,0.00005126196,0.00008547727,0.0000408805,0.0003774317,0.0002548488,0.00001795069],"category_scores_gemma":[0.0001458833,0.0001307232,0.0001155058,0.00005312024,0.0002176819,0.0000108431,0.0001349583,0.0001498997,0.000007054477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002258582,"about_ca_system_score_gemma":0.00009017671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007529666,"about_ca_topic_score_gemma":0.0000135926,"domain_scores_codex":[0.998345,0.00004723977,0.0006629426,0.0001714785,0.0003905486,0.0003827771],"domain_scores_gemma":[0.9989616,0.00002778832,0.0001910651,0.000384383,0.00006014495,0.0003750069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004485792,0.001200235,0.0009172638,0.001732775,0.0003764798,0.00001100338,0.001524476,0.00001034732,0.00594574,0.01859172,0.08099134,0.8882501],"study_design_scores_gemma":[0.003119478,0.007101498,0.00171373,0.0005117518,0.00004197814,0.0001207131,0.009363426,0.004000027,0.03351897,0.0006133316,0.9390326,0.0008624966],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06294553,0.0001436722,0.9327017,0.001390853,0.00033596,0.00116566,0.00003630885,0.0000705694,0.001209728],"genre_scores_gemma":[0.930845,0.0004519441,0.05194586,0.01356799,0.0004522671,0.0009942416,0.0007961724,0.00003412019,0.0009124301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8873876,"threshold_uncertainty_score":0.5330738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393838111215607,"score_gpt":0.339064812332708,"score_spread":0.2996810012111473,"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."}}