{"id":"W4210408999","doi":"10.51731/cjht.2022.250","title":"Idecabtagene Vicleucel (Abecma)","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Health Technologies","topic":"CAR-T cell therapy research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reimbursement; Medicine; Drug; Pharmacology; Intensive care medicine; Health care; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001397581,0.0001066269,0.0003964225,0.001091194,0.000489292,0.00002102483,0.0004388428,0.00006993335,0.002674047],"category_scores_gemma":[0.000347096,0.00009859243,0.000114811,0.000676931,0.0001896215,0.00005392312,0.00006601331,0.001116551,0.00001149869],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001510405,"about_ca_system_score_gemma":0.006392844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004152498,"about_ca_topic_score_gemma":0.001401736,"domain_scores_codex":[0.998229,0.0001023853,0.0005027673,0.000138507,0.0004226686,0.0006046658],"domain_scores_gemma":[0.998983,0.00005161617,0.0002514657,0.0003556896,0.0001540942,0.0002040835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009327933,0.0000409272,0.006661861,0.00008058176,0.00007897709,0.001302148,0.0004474084,0.00003358009,0.004342719,0.0005025915,0.02813018,0.9582857],"study_design_scores_gemma":[0.0009556166,0.001603739,0.005288924,0.00005117805,0.0000105846,0.002607007,0.006704662,0.00001733266,0.002500057,0.0015238,0.9786339,0.0001031492],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6865142,0.1002418,0.0001126357,0.2081657,0.0008796541,0.0006911597,0.00004635358,0.0002081034,0.003140397],"genre_scores_gemma":[0.9957795,0.000471102,0.0004497082,0.00167523,0.00002272875,0.0000142803,0.000003033496,0.00002562427,0.001558856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9581826,"threshold_uncertainty_score":0.99924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0544646208570626,"score_gpt":0.3394416612228756,"score_spread":0.284977040365813,"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."}}