{"id":"W1185454313","doi":"","title":"The Visudyne Registry Database: Collecting Data from Patients Treated with Verteporfin Therapy for CNV due to AMD","year":2004,"lang":"en","type":"article","venue":"","topic":"Cancer Treatment and Pharmacology","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"QLT (Canada)","funders":"","keywords":"Verteporfin; Medicine; Ophthalmology; Macular degeneration; Optometry; Choroidal neovascularization","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":[0.001442704,0.0004992718,0.001534946,0.003973902,0.0004876883,0.001446795,0.0009589823,0.0007259024,0.003761859],"category_scores_gemma":[0.008406369,0.0005811828,0.0007870499,0.008171597,0.0002556299,0.0009331297,0.0009102793,0.0006249844,0.001243118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001609939,"about_ca_system_score_gemma":0.003797559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02677777,"about_ca_topic_score_gemma":0.02288697,"domain_scores_codex":[0.9977906,0.0003805554,0.0006808523,0.000486666,0.000464308,0.0001969628],"domain_scores_gemma":[0.9922381,0.001754791,0.003651018,0.0007959159,0.001037172,0.0005230322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001796063,0.0002844205,0.9361009,0.000677256,0.0006712432,0.0005437513,0.0002348483,0.0005573143,0.001679292,0.0006324091,0.0326811,0.02414128],"study_design_scores_gemma":[0.0009785995,0.0002510614,0.9609929,0.0002659651,0.0006992518,0.001525106,0.0003001804,0.001342395,0.001724767,0.0002148734,0.03164477,0.00006012236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5501321,0.002245191,0.001625972,0.0003835261,0.00007346052,0.0009576271,0.4388132,0.0002441223,0.005524764],"genre_scores_gemma":[0.5062245,0.002245974,0.005243693,0.0005244942,0.0001126841,0.002372961,0.481225,0.0001600931,0.001890647],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02677777,"threshold_uncertainty_score":0.05324382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06628907457578062,"score_gpt":0.3649306742439641,"score_spread":0.2986415996681835,"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."}}