{"id":"W2465278227","doi":"10.1503/cmaj.1150060","title":"Making needles less prickly","year":2015,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Central Venous Catheters and Hemodialysis","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Core (optical fiber); Computer science; Data science; Medicine; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.004831182,0.000981566,0.0009464731,0.0008119708,0.005592351,0.004100829,0.001751567,0.02093033,0.02196085],"category_scores_gemma":[0.05412296,0.0005402469,0.001044889,0.0003654188,0.005104817,0.009196075,0.002576777,0.04377557,0.01521507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00235518,"about_ca_system_score_gemma":0.003451665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006032175,"about_ca_topic_score_gemma":0.01303829,"domain_scores_codex":[0.9941564,0.001836307,0.0004055053,0.0005849872,0.002422837,0.0005938598],"domain_scores_gemma":[0.9828998,0.006021284,0.001039899,0.0007386336,0.005071844,0.004228475],"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":[0.00001297838,0.00002451198,0.0001960537,0.00002859391,0.000006522776,0.0006045345,0.0002122182,0.00001738384,0.00009461588,0.001793086,0.9893284,0.007681038],"study_design_scores_gemma":[0.00001768834,0.00003528367,0.0003176121,0.0002550425,0.000007957126,0.002445903,0.0009241641,0.0000774459,0.00007800718,0.003662667,0.9921471,0.00003117567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.000279454,0.002716507,0.0003726181,0.9596721,0.02905912,0.00001527911,0.00001586782,0.00006757288,0.007801415],"genre_scores_gemma":[0.003331599,0.001390185,0.0005204263,0.9612618,0.01495781,0.00002039668,0.00001373677,0.00004466753,0.0184593],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02196085,"threshold_uncertainty_score":0.07346636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0700307077520249,"score_gpt":0.3538012345137201,"score_spread":0.2837705267616952,"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."}}