{"id":"W3112885733","doi":"10.3389/fpubh.2020.515347","title":"Automatic Identification of Information Quality Metrics in Health News Stories","year":2020,"lang":"en","type":"article","venue":"Frontiers in Public Health","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of Brighton; College of Health, Education, and Human Development, Clemson University","keywords":"Computer science; Quality (philosophy); Artificial intelligence; Health care; Identification (biology); Publication; Process (computing); Machine learning; Task (project management); Natural language; Set (abstract data type); Natural language processing; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009143898,0.001061674,0.000923386,0.01362872,0.000633197,0.003711456,0.0009771028,0.001420292,0.001187652],"category_scores_gemma":[0.0598519,0.0003486589,0.0008251844,0.004104195,0.0006778848,0.003873525,0.001338166,0.001340672,0.00071699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639217,"about_ca_system_score_gemma":0.0009055897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002622659,"about_ca_topic_score_gemma":0.0026788,"domain_scores_codex":[0.991046,0.003211713,0.001428734,0.001430764,0.002485773,0.0003969926],"domain_scores_gemma":[0.9064232,0.06209143,0.01256028,0.002146324,0.01576958,0.001009087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003153197,0.001022183,0.1598748,0.0049119,0.0006571166,0.001247139,0.003878776,0.01453824,0.04178164,0.003722521,0.02854961,0.736663],"study_design_scores_gemma":[0.0002265659,0.001102792,0.2970347,0.0007423739,0.0005260299,0.001367504,0.00402667,0.603225,0.06407798,0.008153184,0.01926989,0.0002473074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.823456,0.005326517,0.1389638,0.002494034,0.0004657869,0.001172402,0.01474999,0.005549347,0.007821988],"genre_scores_gemma":[0.8502414,0.000523526,0.1289891,0.0001293193,0.0002954744,0.0004377265,0.01814989,0.0001589335,0.001074648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01362872,"threshold_uncertainty_score":0.04835814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05770873701829786,"score_gpt":0.3433739866807531,"score_spread":0.2856652496624552,"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."}}