{"id":"W2903980694","doi":"10.1101/496927","title":"Using a diabetes discussion forum and Wikipedia to detect the alignment of public interests and the research literature","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Wikis in Education and Collaboration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Scopus; Latent Dirichlet allocation; Topic model; Original research; Public health; Political science; Library science; MEDLINE; Public relations; Medicine; Computer science; Information retrieval","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.004995401,0.0002171515,0.0002705219,0.0002487833,0.001013366,0.001081103,0.0005815581,0.0002880801,0.00001485334],"category_scores_gemma":[0.002170841,0.0001188398,0.00004995036,0.001196941,0.001286667,0.0002121926,0.0007708562,0.0005030287,0.000003117142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107141,"about_ca_system_score_gemma":0.0008304675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001702993,"about_ca_topic_score_gemma":0.0002338695,"domain_scores_codex":[0.9964333,0.001547462,0.0003340371,0.0005144762,0.0006871002,0.0004836367],"domain_scores_gemma":[0.9973164,0.0003557045,0.0002370823,0.0006951189,0.00117074,0.000224953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006755858,0.0007451207,0.2440454,0.002072694,0.001077681,0.00001268131,0.07126832,0.0000337612,0.3928714,0.2563106,0.02952998,0.001356683],"study_design_scores_gemma":[0.005160195,0.0008604173,0.3807175,0.01079198,0.0007006542,6.79149e-8,0.02659241,0.002823159,0.1337225,0.005521013,0.4287795,0.004330587],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726009,0.002152399,0.0001818053,0.02250969,0.001045702,0.001391858,0.00004235226,0.00004441199,0.00003089957],"genre_scores_gemma":[0.9971684,0.0004677338,0.00112192,0.0002833443,0.0007174464,0.0001985913,1.162114e-7,0.00002838432,0.00001411738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3992495,"threshold_uncertainty_score":0.9999559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05336882479122627,"score_gpt":0.3385828762751554,"score_spread":0.2852140514839291,"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."}}