{"id":"W2038273545","doi":"10.1371/journal.pmed.0040274","title":"Will Spam Overwhelm Our Defenses? Evaluating Offerings for Drugs and Natural Health Products","year":2007,"lang":"en","type":"article","venue":"PLoS Medicine","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto","funders":"","keywords":"Business; Internet privacy; Medicine; Environmental health; Data science; Computer 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":[0.01568948,0.0006271545,0.0007041117,0.002618541,0.001340012,0.004309568,0.000459752,0.002893666,0.006007119],"category_scores_gemma":[0.1022161,0.0002727947,0.0003670116,0.001395189,0.001073141,0.004425774,0.0007689642,0.001561204,0.001982937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002171589,"about_ca_system_score_gemma":0.001649338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005361035,"about_ca_topic_score_gemma":0.007207409,"domain_scores_codex":[0.9879612,0.006715339,0.0003860272,0.000431299,0.003515683,0.0009903547],"domain_scores_gemma":[0.8731278,0.09084643,0.0130154,0.003586909,0.01411188,0.005311558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003141324,0.002861067,0.6412947,0.0003677272,0.0002944942,0.0004851516,0.001906356,0.008307961,0.003445055,0.02532106,0.0832884,0.2292866],"study_design_scores_gemma":[0.0006358724,0.008826492,0.630762,0.0004177039,0.0006387764,0.0006808501,0.01284053,0.1810206,0.019916,0.05208714,0.09191614,0.0002579881],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9381953,0.0008661451,0.004038484,0.01721834,0.0003974211,0.0001903539,0.001048403,0.0002893432,0.03775629],"genre_scores_gemma":[0.9936666,0.0001220998,0.001454486,0.001081552,0.0001861981,0.00003058641,0.0002741101,0.00001898025,0.003165289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01568948,"threshold_uncertainty_score":0.08297485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04171727536953371,"score_gpt":0.3288552280932191,"score_spread":0.2871379527236854,"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."}}