{"id":"W2903220936","doi":"","title":"Research guides: Grey Literature and Statistics for Dentistry: Home","year":2011,"lang":"en","type":"libguides","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grey literature; Oral health; Geography; Statistics; Dentistry; MEDLINE; Medicine; Political science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0006652747,0.0002859291,0.0003364399,0.0001333236,0.0001608132,0.0001667603,0.0004339291,0.00129985,0.00006279347],"category_scores_gemma":[0.001135202,0.000227146,0.0000821763,0.0001136418,0.0005429533,0.000002090145,0.0003639751,0.0004349798,0.00001072394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001221188,"about_ca_system_score_gemma":0.0001980487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005760508,"about_ca_topic_score_gemma":0.0001014605,"domain_scores_codex":[0.9981279,0.000105057,0.0003108635,0.0006845378,0.0002540853,0.0005174906],"domain_scores_gemma":[0.9984735,0.0001549416,0.00009222262,0.000485323,0.0006278421,0.0001661783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006574389,0.000026724,0.00005652231,0.0004637161,0.0001052417,0.00002292891,0.00006428229,1.807763e-8,0.0007026025,0.0008142639,0.9692774,0.02840058],"study_design_scores_gemma":[0.0003793597,0.0007073889,0.0001751987,0.0001922475,0.00003509202,0.00005877251,0.0001192286,0.00000701513,0.001329612,0.005729177,0.990943,0.0003239294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"other","genre_scores_codex":[0.02149474,0.5416582,0.2442207,0.004312763,0.01939999,0.00652125,0.05683293,0.0006475553,0.1049119],"genre_scores_gemma":[0.003376766,0.03203817,0.3556182,0.001081127,0.004672795,0.0003439464,0.01911448,0.0002214648,0.583533],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.50962,"threshold_uncertainty_score":0.9999967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07723222167012465,"score_gpt":0.3789187941579624,"score_spread":0.3016865724878378,"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."}}